diff --git a/404.html b/404.html
index 0a2659aa..1186275d 100644
--- a/404.html
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@@ -14,15 +14,12 @@
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="https://saezlab.github.io/decoupleR/pkgdown.js"></script><link href="https://saezlab.github.io/decoupleR/extra.css" rel="stylesheet">
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+<link href="https://saezlab.github.io/decoupleR/deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="https://saezlab.github.io/decoupleR/deps/headroom-0.11.0/headroom.min.js"></script><script src="https://saezlab.github.io/decoupleR/deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="https://saezlab.github.io/decoupleR/deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="https://saezlab.github.io/decoupleR/deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="https://saezlab.github.io/decoupleR/deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="https://saezlab.github.io/decoupleR/deps/search-1.0.0/fuse.min.js"></script><script src="https://saezlab.github.io/decoupleR/deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="https://saezlab.github.io/decoupleR/pkgdown.js"></script><link href="https://saezlab.github.io/decoupleR/extra.css" rel="stylesheet">
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@@ -32,73 +29,48 @@
 </head>
 <body>
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-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="https://saezlab.github.io/decoupleR/index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
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-<li class="nav-item">
-  <a class="nav-link" href="https://saezlab.github.io/decoupleR/reference/index.html">Reference</a>
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+<li class="nav-item"><a class="nav-link" href="https://saezlab.github.io/decoupleR/articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="https://saezlab.github.io/decoupleR/reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
-  <a href="https://saezlab.github.io/decoupleR/#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="https://saezlab.github.io/decoupleR/news/index.html">Changelog</a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="https://saezlab.github.io/decoupleR/articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="https://saezlab.github.io/decoupleR/news/index.html">Changelog</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
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+<ul class="navbar-nav">
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul>
 </div>
 
-    
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   </div>
 </nav><div class="container template-title-body">
 <div class="row">
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-      
+
     </div>
 
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@@ -108,21 +80,19 @@
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer>
 </div>
 
-  
 
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diff --git a/LICENSE-text.html b/LICENSE-text.html
index ec6e6652..1fca7043 100644
--- a/LICENSE-text.html
+++ b/LICENSE-text.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>License • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><meta property="og:title" content="License"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>License • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><meta property="og:title" content="License"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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   gtag('js', new Date());
@@ -10,68 +7,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
 
     <div id="navbar" class="collapse navbar-collapse ms-3">
-      <ul class="navbar-nav me-auto"><li class="nav-item">
-  <a class="nav-link" href="articles/decoupleR.html">Get started</a>
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-<li class="nav-item">
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="reference/index.html">Reference</a></li>
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-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="news/index.html">Changelog</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
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-  <a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="github">
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-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
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 </nav><div class="container template-title-body">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="logo.svg" class="logo" alt=""><h1>License</h1>
-      
+
     </div>
 
 <pre>                    GNU GENERAL PUBLIC LICENSE
@@ -754,18 +725,18 @@
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/articles/decoupleR.html b/articles/decoupleR.html
index 14e4b7f9..f027c912 100644
--- a/articles/decoupleR.html
+++ b/articles/decoupleR.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
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 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
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+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <meta property="og:title" content="Introduction">
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@@ -34,67 +28,42 @@
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 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+<li class="active nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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+<ul class="navbar-nav">
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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 </nav><div class="container template-article">
 
@@ -111,7 +80,7 @@ <h4 data-toc-skip class="author">Pau
 Universiy<br><h4 data-toc-skip class="author">Jesús
 Vélez-Santiago</h4>
             <address class="author_afil">
-      National Autonomous University of Mexico<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/vignettes/decoupleR.Rmd" class="external-link"><code>vignettes/decoupleR.Rmd</code></a></small>
+      National Autonomous University of Mexico<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/vignettes/decoupleR.Rmd" class="external-link"><code>vignettes/decoupleR.Rmd</code></a></small>
       <div class="d-none name"><code>decoupleR.Rmd</code></div>
     </address>
 </address>
@@ -122,7 +91,7 @@ <h4 data-toc-skip class="author">Pau
 <div class="section level2">
 <h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>
 </h2>
-<p><em><a href="https://bioconductor.org/packages/3.19/decoupleR" class="external-link">decoupleR</a></em>
+<p><em><a href="https://bioconductor.org/packages/3.20/decoupleR" class="external-link">decoupleR</a></em>
 is an R package distributed as part of the Bioconductor project. To
 install the package, start R and enter:</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
@@ -136,7 +105,7 @@ <h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#i
 <div class="section level2">
 <h2 id="usage">Usage<a class="anchor" aria-label="anchor" href="#usage"></a>
 </h2>
-<p><em><a href="https://bioconductor.org/packages/3.19/decoupleR" class="external-link">decoupleR</a></em>
+<p><em><a href="https://bioconductor.org/packages/3.20/decoupleR" class="external-link">decoupleR</a></em>
 (Badia-i-Mompel, Santiago, Braunger, Geiss, Dimitrov, Müller-Dott, Taus,
 Dugourd, Holland, Flores, and Saez-Rodriguez, 2022) contains different
 statistical methods to extract biological activities from omics data
@@ -154,7 +123,7 @@ <h2 id="usage">Usage<a class="anchor" aria-label="anchor" href="#usage"></a>
 <div class="section level3">
 <h3 id="libraries">Libraries<a class="anchor" aria-label="anchor" href="#libraries"></a>
 </h3>
-<p><em><a href="https://bioconductor.org/packages/3.19/decoupleR" class="external-link">decoupleR</a></em>
+<p><em><a href="https://bioconductor.org/packages/3.20/decoupleR" class="external-link">decoupleR</a></em>
 can be imported as:</p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://saezlab.github.io/decoupleR/">decoupleR</a></span><span class="op">)</span></span>
@@ -166,7 +135,7 @@ <h3 id="libraries">Libraries<a class="anchor" aria-label="anchor" href="#librari
 <div class="section level3">
 <h3 id="input-data">Input data<a class="anchor" aria-label="anchor" href="#input-data"></a>
 </h3>
-<p><em><a href="https://bioconductor.org/packages/3.19/decoupleR" class="external-link">decoupleR</a></em>
+<p><em><a href="https://bioconductor.org/packages/3.20/decoupleR" class="external-link">decoupleR</a></em>
 needs a matrix (<code>mat</code>) of any molecular readouts (gene
 expression, logFC, p-values, etc.) and a <code>network</code> that
 relates target features (genes, proteins, etc.) to “source” biological
@@ -175,7 +144,7 @@ <h3 id="input-data">Input data<a class="anchor" aria-label="anchor" href="#input
 interaction, defined as negative or positive weights.</p>
 <p>To get an example data-set, run:</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/get_toy_data.html">get_toy_data</a></span><span class="op">(</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/get_toy_data.html">get_toy_data</a></span><span class="op">(</span><span class="op">)</span></span>
 <span></span>
 <span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">mat</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">mat</span>,<span class="fl">5</span><span class="op">)</span><span class="op">[</span>,<span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">]</span></span>
@@ -204,7 +173,20 @@ <h3 id="input-data">Input data<a class="anchor" aria-label="anchor" href="#input
 <p>This example consists of two small populations of samples (S, cols)
 with different gene expression patterns (G, rows):</p>
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">mat</span>, cluster_rows <span class="op">=</span> <span class="cn">F</span>, cluster_cols <span class="op">=</span> <span class="cn">F</span><span class="op">)</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="co"># Color scale</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Heatmap</span></span>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   cluster_rows <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cluster_cols <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">15</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">15</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">0</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span></code></pre></div>
 <p><img src="decoupleR_files/figure-html/show_matrix-1.png" width="700"></p>
 <p>Here we can see that some genes seem to be more expressed in one
 group of samples than in the other and vice-versa. Ideally, we would
@@ -223,10 +205,10 @@ <h3 id="input-data">Input data<a class="anchor" aria-label="anchor" href="#input
 <div class="section level3">
 <h3 id="methods">Methods<a class="anchor" aria-label="anchor" href="#methods"></a>
 </h3>
-<p><em><a href="https://bioconductor.org/packages/3.19/decoupleR" class="external-link">decoupleR</a></em>
+<p><em><a href="https://bioconductor.org/packages/3.20/decoupleR" class="external-link">decoupleR</a></em>
 contains several methods. To check how many are available, run:</p>
 <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/show_methods.html">show_methods</a></span><span class="op">(</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/show_methods.html">show_methods</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 12 × 2</span></span></span>
 <span><span class="co">#&gt;    Function      Name                                                           </span></span>
 <span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                                                          </span></span>
@@ -284,7 +266,12 @@ <h4 id="individual-methods">Individual methods<a class="anchor" aria-label="anch
 <p>As an example, let’s first run the Gene Set Enrichment Analysis
 method (<code>gsea</code>), one of the most well-known statistics:</p>
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">res_gsea</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_fgsea.html">run_fgsea</a></span><span class="op">(</span><span class="va">mat</span>, <span class="va">network</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>, nproc<span class="op">=</span><span class="fl">1</span>, minsize <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">res_gsea</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_fgsea.html">run_fgsea</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat</span>, </span>
+<span>                                 network <span class="op">=</span> <span class="va">network</span>, </span>
+<span>                                 .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                 .target <span class="op">=</span> <span class="st">'target'</span>, </span>
+<span>                                 nproc <span class="op">=</span> <span class="fl">1</span>, </span>
+<span>                                 minsize <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span>
 <span><span class="co">#&gt;   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt;   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100%</span></span>
@@ -332,6 +319,7 @@ <h4 id="individual-methods">Individual methods<a class="anchor" aria-label="anch
 <span><span class="co">#&gt;   |                                                                              |                                                                      |   0%  |                                                                              |===================================                                   |  50%  |                                                                              |======================================================================| 100%</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt;   |                                                                              |                                                                      |   0%  |                                                                              |===================================                                   |  50%  |                                                                              |======================================================================| 100%</span></span>
+<span></span>
 <span><span class="va">res_gsea</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 144 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic  source condition   score p_value</span></span>
@@ -368,7 +356,13 @@ <h4 id="individual-methods">Individual methods<a class="anchor" aria-label="anch
 <p>Other methods can return different things, for example Univariate
 Linear Model (<code>ulm</code>):</p>
 <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">res_ulm</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span><span class="va">mat</span>, <span class="va">network</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>, .mor<span class="op">=</span><span class="st">'mor'</span>, minsize <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">res_ulm</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat</span>, </span>
+<span>                              network <span class="op">=</span> <span class="va">network</span>, </span>
+<span>                              .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                              .target <span class="op">=</span> <span class="st">'target'</span>, </span>
+<span>                              .mor <span class="op">=</span> <span class="st">'mor'</span>, </span>
+<span>                              minsize <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">res_ulm</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 72 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source condition score  p_value</span></span>
@@ -392,12 +386,26 @@ <h4 id="individual-methods">Individual methods<a class="anchor" aria-label="anch
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Transform to matrix</span></span>
 <span><span class="va">mat_gsea</span> <span class="op">&lt;-</span> <span class="va">res_gsea</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">statistic</span><span class="op">==</span><span class="st">'fgsea'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/pivot_wider_profile.html">pivot_wider_profile</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="va">source</span>, names_from <span class="op">=</span> <span class="va">condition</span>, </span>
-<span>                      values_from <span class="op">=</span> <span class="va">score</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>            <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">statistic</span> <span class="op">==</span> <span class="st">'fgsea'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>            <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/pivot_wider_profile.html">pivot_wider_profile</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="va">source</span>, </span>
+<span>                                           names_from <span class="op">=</span> <span class="va">condition</span>, </span>
+<span>                                           values_from <span class="op">=</span> <span class="va">score</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>            <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Color scale</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">mat_gsea</span>, cluster_rows <span class="op">=</span> <span class="cn">F</span>, cluster_cols <span class="op">=</span> <span class="cn">F</span>, cellwidth <span class="op">=</span> <span class="fl">15</span>, cellheight <span class="op">=</span> <span class="fl">40</span><span class="op">)</span></span></code></pre></div>
+<span><span class="co"># Heatmap</span></span>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat_gsea</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   cluster_rows <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cluster_cols <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">0</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span></code></pre></div>
 <p><img src="decoupleR_files/figure-html/res_gsea-1.png" width="700"></p>
 <p>We can observe that for transcription factors T1 and T2, the obtained
 activities correctly distinguish the two sample populations. T3, on the
@@ -411,12 +419,26 @@ <h4 id="individual-methods">Individual methods<a class="anchor" aria-label="anch
 <div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Transform to matrix</span></span>
 <span><span class="va">mat_ulm</span> <span class="op">&lt;-</span> <span class="va">res_ulm</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">statistic</span><span class="op">==</span><span class="st">'ulm'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/pivot_wider_profile.html">pivot_wider_profile</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="va">source</span>, names_from <span class="op">=</span> <span class="va">condition</span>, </span>
-<span>                      values_from <span class="op">=</span> <span class="va">score</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>           <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">statistic</span><span class="op">==</span><span class="st">'ulm'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>           <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/pivot_wider_profile.html">pivot_wider_profile</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="va">source</span>, </span>
+<span>                                          names_from <span class="op">=</span> <span class="va">condition</span>, </span>
+<span>                                          values_from <span class="op">=</span> <span class="va">score</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>           <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Color scale</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">mat_ulm</span>, cluster_rows <span class="op">=</span> <span class="cn">F</span>, cluster_cols <span class="op">=</span> <span class="cn">F</span>, cellwidth <span class="op">=</span> <span class="fl">15</span>, cellheight <span class="op">=</span> <span class="fl">40</span><span class="op">)</span></span></code></pre></div>
+<span><span class="co"># Heatmap</span></span>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat_ulm</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   cluster_rows <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cluster_cols <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">0</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span></code></pre></div>
 <p><img src="decoupleR_files/figure-html/res_ulm-1.png" width="700"></p>
 <p>Since <code>ulm</code> models weights when estimating biological
 activities, it correctly assigns T3 as inactive in the second population
@@ -425,7 +447,7 @@ <h4 id="individual-methods">Individual methods<a class="anchor" aria-label="anch
 <div class="section level4">
 <h4 id="multiple-methods">Multiple methods<a class="anchor" aria-label="anchor" href="#multiple-methods"></a>
 </h4>
-<p><em><a href="https://bioconductor.org/packages/3.19/decoupleR" class="external-link">decoupleR</a></em>
+<p><em><a href="https://bioconductor.org/packages/3.20/decoupleR" class="external-link">decoupleR</a></em>
 also allows to run multiple methods at the same time. Moreover, it
 computes a consensus score based on the obtained activities across
 methods, called <code>consensus</code>.</p>
@@ -436,11 +458,12 @@ <h4 id="multiple-methods">Multiple methods<a class="anchor" aria-label="anchor"
 <code>args</code>. For more information check
 <code><a href="../reference/decouple.html">?decouple</a></code>.</p>
 <div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">res_decouple</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/decouple.html">decouple</a></span><span class="op">(</span><span class="va">mat</span>, </span>
-<span>                         <span class="va">network</span>, </span>
-<span>                         .source<span class="op">=</span><span class="st">'source'</span>, </span>
-<span>                         .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                         minsize <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">res_decouple</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/decouple.html">decouple</a></span><span class="op">(</span><span class="va">mat</span>, </span>
+<span>                                    <span class="va">network</span>, </span>
+<span>                                    .source <span class="op">=</span><span class="st">'source'</span>, </span>
+<span>                                    .target <span class="op">=</span><span class="st">'target'</span>,</span>
+<span>                                    minsize <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">res_decouple</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 432 × 6</span></span></span>
 <span><span class="co">#&gt;    run_id statistic source condition   score p_value</span></span>
@@ -461,12 +484,25 @@ <h4 id="multiple-methods">Multiple methods<a class="anchor" aria-label="anchor"
 <div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Transform to matrix</span></span>
 <span><span class="va">mat_consensus</span> <span class="op">&lt;-</span> <span class="va">res_decouple</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">statistic</span><span class="op">==</span><span class="st">'consensus'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/pivot_wider_profile.html">pivot_wider_profile</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="va">source</span>, names_from <span class="op">=</span> <span class="va">condition</span>, </span>
-<span>                      values_from <span class="op">=</span> <span class="va">score</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>                 <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">statistic</span> <span class="op">==</span> <span class="st">'consensus'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                 <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/pivot_wider_profile.html">pivot_wider_profile</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="va">source</span>, </span>
+<span>                                                names_from <span class="op">=</span> <span class="va">condition</span>, </span>
+<span>                                                values_from <span class="op">=</span> <span class="va">score</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                 <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="co"># Color scale</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">mat_consensus</span>, cluster_rows <span class="op">=</span> <span class="cn">F</span>, cluster_cols <span class="op">=</span> <span class="cn">F</span>, cellwidth <span class="op">=</span> <span class="fl">15</span>, cellheight <span class="op">=</span> <span class="fl">40</span><span class="op">)</span></span></code></pre></div>
+<span><span class="co"># Heatmap</span></span>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat_consensus</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   cluster_rows <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cluster_cols <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">0</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">0</span><span class="op">)</span></span></code></pre></div>
 <p><img src="decoupleR_files/figure-html/res_decouple-1.png" width="700"></p>
 <p>We can observe that the consensus score correctly predicts that T1
 and T3 should be active in the first population of samples while T2 in
@@ -479,91 +515,90 @@ <h2 id="session-information">Session information<a class="anchor" aria-label="an
 </h2>
 <pre><code><span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
 <span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">setting </span> <span style="color: #555555; font-style: italic;">value</span></span></span>
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+<span><span class="co">#&gt;  version  R version 4.4.1 (2024-06-14)</span></span>
+<span><span class="co">#&gt;  os       Ubuntu 22.04.5 LTS</span></span>
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 <span><span class="co">#&gt;  language en</span></span>
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+<span><span class="co">#&gt;  date     2024-10-19</span></span>
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 <span><span class="co">#&gt; </span></span>
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-<span><span class="co">#&gt;  pillar         1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgconfig      2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgdown        2.0.8   <span style="color: #555555;">2024-04-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  plyr           1.8.9   <span style="color: #555555;">2023-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  purrr          1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  R6             2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ragg           1.3.0   <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RColorBrewer   1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  tibble         3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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+<span><span class="co">#&gt;  backports      1.5.0   <span style="color: #555555;">2024-05-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
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+<span><span class="co">#&gt;  BiocParallel   1.38.0  <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
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+<span><span class="co">#&gt;  codetools      0.2-20  <span style="color: #555555;">2024-03-31</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  colorspace     2.1-1   <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cowplot        1.1.3   <span style="color: #555555;">2024-01-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  data.table     1.16.2  <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  decoupleR    * 2.9.7   <span style="color: #555555;">2024-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">Bioconductor</span></span></span>
+<span><span class="co">#&gt;  desc           1.4.3   <span style="color: #555555;">2023-12-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  digest         0.6.37  <span style="color: #555555;">2024-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dplyr        * 1.1.4   <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  evaluate       1.0.1   <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fansi          1.0.6   <span style="color: #555555;">2023-12-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastmap        1.2.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastmatch      1.1-4   <span style="color: #555555;">2023-08-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fgsea          1.30.0  <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  fs             1.6.4   <span style="color: #555555;">2024-04-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  generics       0.1.3   <span style="color: #555555;">2022-07-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggplot2        3.5.1   <span style="color: #555555;">2024-04-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  glue           1.8.0   <span style="color: #555555;">2024-09-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gtable         0.3.5   <span style="color: #555555;">2024-04-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  highr          0.11    <span style="color: #555555;">2024-05-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmltools      0.5.8.1 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmlwidgets    1.6.4   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httr           1.4.7   <span style="color: #555555;">2023-08-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jquerylib      0.1.4   <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jsonlite       1.8.9   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  knitr          1.48    <span style="color: #555555;">2024-07-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lattice        0.22-6  <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  lifecycle      1.0.4   <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lubridate      1.9.3   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  magrittr       2.0.3   <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Matrix         1.7-1   <span style="color: #555555;">2024-10-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  munsell        0.5.1   <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  parallelly     1.38.0  <span style="color: #555555;">2024-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pheatmap     * 1.0.12  <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pillar         1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgconfig      2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgdown        2.1.1   <span style="color: #555555;">2024-09-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  plyr           1.8.9   <span style="color: #555555;">2023-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  purrr          1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  R6             2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ragg           1.3.3   <span style="color: #555555;">2024-09-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RColorBrewer   1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rcpp           1.0.13  <span style="color: #555555;">2024-07-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RefManageR   * 1.4.0   <span style="color: #555555;">2022-09-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rlang          1.1.4   <span style="color: #555555;">2024-06-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rmarkdown      2.28    <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sass           0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scales         1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sessioninfo    1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringi        1.8.4   <span style="color: #555555;">2024-05-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringr        1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  systemfonts    1.1.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  textshaping    0.4.0   <span style="color: #555555;">2024-05-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tibble         3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyr          1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyselect     1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  timechange     0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  utf8           1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vctrs          0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  withr          3.0.1   <span style="color: #555555;">2024-07-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xfun           0.48    <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xml2           1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  yaml           2.3.10  <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [1] /usr/local/lib/R/site-library</span></span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [2] /usr/local/lib/R/library</span></span></span>
@@ -611,28 +646,26 @@ <h2 id="bibliography">Bibliography<a class="anchor" aria-label="anchor" href="#b
 <a href="http://biorxiv.org/content/early/2016/06/20/060012" class="external-link">http://biorxiv.org/content/early/2016/06/20/060012</a>.</cite>
 </p>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
 
 
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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+++ b/articles/index.html
@@ -1,8 +1,5 @@
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Articles"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
   window.dataLayer = window.dataLayer || [];
   function gtag(){dataLayer.push(arguments);}
   gtag('js', new Date());
@@ -10,62 +7,36 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
-    
+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
 
     <div id="navbar" class="collapse navbar-collapse ms-3">
-      <ul class="navbar-nav me-auto"><li class="nav-item">
-  <a class="nav-link" href="../articles/decoupleR.html">Get started</a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">Reference</a>
-</li>
+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
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-  <a class="external-link nav-link" href="https://www.saezlab.org">
-    <span class="fas fa fas fa-university"></span>
-     
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-article-index">
 <div class="row">
@@ -75,7 +46,7 @@
 
     <div class="section ">
       <h3>All vignettes</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="decoupleR.html">Introduction</a></dt>
         <dd>
@@ -92,18 +63,18 @@ <h3>All vignettes</h3>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/articles/pw_bk.html b/articles/pw_bk.html
index 436a7e8f..be7b32d3 100644
--- a/articles/pw_bk.html
+++ b/articles/pw_bk.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="decoupleR">
 <title>Pathway activity inference in bulk RNA-seq • decoupleR</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -15,16 +14,11 @@
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 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <meta property="og:title" content="Pathway activity inference in bulk RNA-seq">
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-<meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg">
-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
   window.dataLayer = window.dataLayer || [];
   function gtag(){dataLayer.push(arguments);}
   gtag('js', new Date());
@@ -34,67 +28,42 @@
 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
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       <ul class="navbar-nav me-auto">
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-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">Reference</a>
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+<li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
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+<ul class="navbar-nav">
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
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       </ul>
 </div>
 
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+
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 </nav><div class="container template-article">
 
@@ -107,7 +76,7 @@
                         <h4 data-toc-skip class="author">Pau
 Badia-i-Mompel</h4>
             <address class="author_afil">
-      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/vignettes/pw_bk.Rmd" class="external-link"><code>vignettes/pw_bk.Rmd</code></a></small>
+      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/vignettes/pw_bk.Rmd" class="external-link"><code>vignettes/pw_bk.Rmd</code></a></small>
       <div class="d-none name"><code>pw_bk.Rmd</code></div>
     </address>
 </div>
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 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
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-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"gene"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>          <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span><span class="op">)</span>, </span>
+<span>                           <span class="op">~</span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/if_else.html" class="external-link">if_else</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span>, <span class="fl">0</span>, <span class="va">.x</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>          <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"gene"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>          <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">counts</span><span class="op">)</span></span>
 <span><span class="co">#&gt;          PANC1.WT.Rep1 PANC1.WT.Rep2 PANC1.WT.Rep3 PANC1.FOXA2KO.Rep1</span></span>
 <span><span class="co">#&gt; NOC2L        10.052588     11.949123     12.057774          12.312291</span></span>
@@ -184,6 +155,7 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <p>The design meta-data:</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">design</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">design</span></span>
+<span></span>
 <span><span class="va">design</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 2</span></span></span>
 <span><span class="co">#&gt;   sample             condition    </span></span>
@@ -199,10 +171,11 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Extract t-values per gene</span></span>
 <span><span class="va">deg</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">limma_ttop</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">ID</span>, <span class="va">t</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">t</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>    <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"ID"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">ID</span>, <span class="va">t</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">t</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>       <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"ID"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">deg</span><span class="op">)</span></span>
 <span><span class="co">#&gt;                  t</span></span>
 <span><span class="co">#&gt; RHBDL2  -12.810588</span></span>
@@ -265,7 +238,9 @@ <h2 id="progeny-model">PROGENy model<a class="anchor" aria-label="anchor" href="
 </ul>
 <p>To access it we can use <code>decoupleR</code>:</p>
 <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/get_progeny.html">get_progeny</a></span><span class="op">(</span>organism <span class="op">=</span> <span class="st">'human'</span>, top <span class="op">=</span> <span class="fl">500</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/get_progeny.html">get_progeny</a></span><span class="op">(</span>organism <span class="op">=</span> <span class="st">'human'</span>, </span>
+<span>                              top <span class="op">=</span> <span class="fl">500</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">net</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 7,000 × 4</span></span></span>
 <span><span class="co">#&gt;    source   target  weight  p_value</span></span>
@@ -301,8 +276,12 @@ <h2 id="activity-inference-with-multivariate-linear-model-mlm">Activity inferenc
 use.</p>
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Run mlm</span></span>
-<span><span class="va">sample_acts</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_mlm.html">run_mlm</a></span><span class="op">(</span>mat<span class="op">=</span><span class="va">counts</span>, net<span class="op">=</span><span class="va">net</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                  .mor<span class="op">=</span><span class="st">'weight'</span>, minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span><span class="va">sample_acts</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_mlm.html">run_mlm</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">counts</span>, </span>
+<span>                                  net <span class="op">=</span> <span class="va">net</span>, </span>
+<span>                                  .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                  .target <span class="op">=</span> <span class="st">'target'</span>,</span>
+<span>                                  .mor <span class="op">=</span> <span class="st">'weight'</span>, </span>
+<span>                                  minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
 <span><span class="va">sample_acts</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 84 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source   condition       score  p_value</span></span>
@@ -327,30 +306,43 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Transform to wide matrix</span></span>
 <span><span class="va">sample_acts_mat</span> <span class="op">&lt;-</span> <span class="va">sample_acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'condition'</span>, names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
-<span>              values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'condition'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>                   <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'condition'</span>, </span>
+<span>                                      names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
+<span>                                      values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                   <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'condition'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                   <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Scale per feature</span></span>
 <span><span class="va">sample_acts_mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/scale.html" class="external-link">scale</a></span><span class="op">(</span><span class="va">sample_acts_mat</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># Choose color palette</span></span>
-<span><span class="va">palette_length</span> <span class="op">=</span> <span class="fl">100</span></span>
-<span><span class="va">my_color</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Darkblue"</span>, <span class="st">"white"</span>,<span class="st">"red"</span><span class="op">)</span><span class="op">)</span><span class="op">(</span><span class="va">palette_length</span><span class="op">)</span></span>
+<span><span class="co"># Color scale</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">3</span>, <span class="fl">0</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
-<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">3</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">2</span>, <span class="fl">0</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
+<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>,<span class="fl">2</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Plot</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">sample_acts_mat</span>, border_color <span class="op">=</span> <span class="cn">NA</span>, color<span class="op">=</span><span class="va">my_color</span>, breaks <span class="op">=</span> <span class="va">my_breaks</span><span class="op">)</span> </span></code></pre></div>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">sample_acts_mat</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   breaks <span class="op">=</span> <span class="va">my_breaks</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">20</span><span class="op">)</span></span></code></pre></div>
 <p><img src="pw_bk_files/figure-html/heatmap-1.png" width="700"></p>
 <p>We can also infer pathway activities from the t-values of the DEGs
 between KO and WT:</p>
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Run mlm</span></span>
-<span><span class="va">contrast_acts</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_mlm.html">run_mlm</a></span><span class="op">(</span>mat<span class="op">=</span><span class="va">deg</span>, net<span class="op">=</span><span class="va">net</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                  .mor<span class="op">=</span><span class="st">'weight'</span>, minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span><span class="va">contrast_acts</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_mlm.html">run_mlm</a></span><span class="op">(</span>mat  <span class="op">=</span><span class="va">deg</span>, </span>
+<span>                                    net <span class="op">=</span> <span class="va">net</span>, </span>
+<span>                                    .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                    .target <span class="op">=</span> <span class="st">'target'</span>,</span>
+<span>                                    .mor <span class="op">=</span> <span class="st">'weight'</span>, </span>
+<span>                                    minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">contrast_acts</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 14 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source   condition  score  p_value</span></span>
@@ -372,18 +364,31 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 <p>Let’s show the changes in activity between KO and WT:</p>
 <div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Plot</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">contrast_acts</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/reorder.factor.html" class="external-link">reorder</a></span><span class="op">(</span><span class="va">source</span>, <span class="va">score</span><span class="op">)</span>, y <span class="op">=</span> <span class="va">score</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_bar</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>fill <span class="op">=</span> <span class="va">score</span><span class="op">)</span>, stat <span class="op">=</span> <span class="st">"identity"</span><span class="op">)</span> <span class="op">+</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_gradient.html" class="external-link">scale_fill_gradient2</a></span><span class="op">(</span>low <span class="op">=</span> <span class="st">"darkblue"</span>, high <span class="op">=</span> <span class="st">"indianred"</span>, </span>
-<span>        mid <span class="op">=</span> <span class="st">"whitesmoke"</span>, midpoint <span class="op">=</span> <span class="fl">0</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
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 <p><img src="pw_bk_files/figure-html/barplot-1.png" width="700"></p>
 <p>The pathway p53 and Trail are deactivated in KO when compared to WT,
 while MAPKK and JAK-STAT and seem to be activated.</p>
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-<span>  <span class="fu"><a href="https://ggrepel.slowkow.com/reference/geom_text_repel.html" class="external-link">geom_label_repel</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>label <span class="op">=</span> <span class="va">ID</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
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+<span>                                            y <span class="op">=</span> <span class="va">t_value</span>, </span>
+<span>                                            color <span class="op">=</span> <span class="va">color</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
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+<span>                         color <span class="op">=</span> <span class="st">"black"</span><span class="op">)</span> <span class="op">+</span> </span>
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+<span>     <span class="fu">ggrepel</span><span class="fu">::</span><span class="fu"><a href="https://ggrepel.slowkow.com/reference/geom_text_repel.html" class="external-link">geom_label_repel</a></span><span class="op">(</span>mapping <span class="op">=</span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>label <span class="op">=</span> <span class="va">ID</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
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+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span>xintercept <span class="op">=</span> <span class="fl">0</span>, linetype <span class="op">=</span> <span class="st">'dotted'</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_hline</a></span><span class="op">(</span>yintercept <span class="op">=</span> <span class="fl">0</span>, linetype <span class="op">=</span> <span class="st">'dotted'</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="va">pathway</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p</span></span>
 <span><span class="co">#&gt; Warning: ggrepel: 447 unlabeled data points (too many overlaps). Consider</span></span>
 <span><span class="co">#&gt; increasing max.overlaps</span></span></code></pre></div>
 <p><img src="pw_bk_files/figure-html/targets-1.png" width="700"></p>
@@ -428,135 +448,132 @@ <h2 id="session-information">Session information<a class="anchor" aria-label="an
 </h2>
 <pre><code><span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
 <span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">setting </span> <span style="color: #555555; font-style: italic;">value</span></span></span>
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-<span><span class="co">#&gt;  os       Ubuntu 22.04.4 LTS</span></span>
+<span><span class="co">#&gt;  version  R version 4.4.1 (2024-06-14)</span></span>
+<span><span class="co">#&gt;  os       Ubuntu 22.04.5 LTS</span></span>
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 <span><span class="co">#&gt;  language en</span></span>
 <span><span class="co">#&gt;  collate  en_US.UTF-8</span></span>
 <span><span class="co">#&gt;  ctype    en_US.UTF-8</span></span>
 <span><span class="co">#&gt;  tz       UTC</span></span>
-<span><span class="co">#&gt;  date     2024-04-11</span></span>
-<span><span class="co">#&gt;  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown)</span></span>
+<span><span class="co">#&gt;  date     2024-10-19</span></span>
+<span><span class="co">#&gt;  pandoc   3.4 @ /usr/bin/ (via rmarkdown)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
 <span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">package     </span> <span style="color: #555555; font-style: italic;">*</span> <span style="color: #555555; font-style: italic;">version</span> <span style="color: #555555; font-style: italic;">date (UTC)</span> <span style="color: #555555; font-style: italic;">lib</span> <span style="color: #555555; font-style: italic;">source</span></span></span>
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-<span><span class="co">#&gt;  cachem         1.0.8   <span style="color: #555555;">2023-05-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  colorspace     2.1-0   <span style="color: #555555;">2023-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  crayon         1.5.2   <span style="color: #555555;">2022-09-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  curl           5.2.1   <span style="color: #555555;">2024-03-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  dplyr        * 1.1.4   <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  evaluate       0.23    <span style="color: #555555;">2023-11-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  fansi          1.0.6   <span style="color: #555555;">2023-12-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  farver         2.1.1   <span style="color: #555555;">2022-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  fastmap        1.1.1   <span style="color: #555555;">2023-02-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  fs             1.6.3   <span style="color: #555555;">2023-07-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  logger         0.3.0   <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  magrittr       2.0.3   <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Matrix         1.7-0   <span style="color: #555555;">2024-03-22</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  memoise        2.0.1   <span style="color: #555555;">2021-11-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  OmnipathR      3.11.10 <span style="color: #555555;">2024-03-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
-<span><span class="co">#&gt;  parallelly     1.37.1  <span style="color: #555555;">2024-02-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pheatmap     * 1.0.12  <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pillar         1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgconfig      2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgdown        2.0.8   <span style="color: #555555;">2024-04-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  prettyunits    1.2.0   <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  progress       1.2.3   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  purrr          1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  R6             2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ragg           1.3.0   <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rappdirs       0.3.3   <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RColorBrewer   1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Rcpp           1.0.12  <span style="color: #555555;">2024-01-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readr          2.1.5   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readxl         1.4.3   <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rlang          1.1.3   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rmarkdown      2.26    <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rvest          1.0.4   <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sass           0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  scales         1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  selectr        0.4-2   <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sessioninfo    1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringi        1.8.3   <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringr        1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  systemfonts    1.0.6   <span style="color: #555555;">2024-03-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  textshaping    0.3.7   <span style="color: #555555;">2023-10-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tibble       * 3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyr        * 1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyselect     1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  timechange     0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tzdb           0.4.0   <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  utf8           1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vctrs          0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vroom          1.6.5   <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  withr          3.0.0   <span style="color: #555555;">2024-01-16</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xfun           0.43    <span style="color: #555555;">2024-03-25</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xml2           1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  yaml           2.3.8   <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
+<span><span class="co">#&gt;  backports      1.5.0   <span style="color: #555555;">2024-05-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocManager    1.30.25 <span style="color: #555555;">2024-08-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocParallel   1.38.0  <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  BiocStyle    * 2.32.1  <span style="color: #555555;">2024-06-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  bit            4.5.0   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bit64          4.5.2   <span style="color: #555555;">2024-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bookdown       0.41    <span style="color: #555555;">2024-10-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bslib          0.8.0   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cachem         1.1.0   <span style="color: #555555;">2024-05-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cellranger     1.1.0   <span style="color: #555555;">2016-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  checkmate      2.3.2   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cli            3.6.3   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  codetools      0.2-20  <span style="color: #555555;">2024-03-31</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  colorspace     2.1-1   <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  crayon         1.5.3   <span style="color: #555555;">2024-06-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  curl           5.2.3   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  decoupleR    * 2.9.7   <span style="color: #555555;">2024-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">Bioconductor</span></span></span>
+<span><span class="co">#&gt;  desc           1.4.3   <span style="color: #555555;">2023-12-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  digest         0.6.37  <span style="color: #555555;">2024-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dplyr        * 1.1.4   <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  evaluate       1.0.1   <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fansi          1.0.6   <span style="color: #555555;">2023-12-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  farver         2.1.2   <span style="color: #555555;">2024-05-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastmap        1.2.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fs             1.6.4   <span style="color: #555555;">2024-04-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  generics       0.1.3   <span style="color: #555555;">2022-07-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggplot2      * 3.5.1   <span style="color: #555555;">2024-04-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggrepel      * 0.9.6   <span style="color: #555555;">2024-09-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  glue           1.8.0   <span style="color: #555555;">2024-09-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gtable         0.3.5   <span style="color: #555555;">2024-04-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  highr          0.11    <span style="color: #555555;">2024-05-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  hms            1.1.3   <span style="color: #555555;">2023-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmltools      0.5.8.1 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmlwidgets    1.6.4   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httr           1.4.7   <span style="color: #555555;">2023-08-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  igraph         2.0.3   <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jquerylib      0.1.4   <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jsonlite       1.8.9   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  knitr          1.48    <span style="color: #555555;">2024-07-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  labeling       0.4.3   <span style="color: #555555;">2023-08-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  later          1.3.2   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lattice        0.22-6  <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  lifecycle      1.0.4   <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  logger         0.3.0   <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lubridate      1.9.3   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  magrittr       2.0.3   <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Matrix         1.7-1   <span style="color: #555555;">2024-10-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  munsell        0.5.1   <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  OmnipathR      3.12.4  <span style="color: #555555;">2024-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  parallelly     1.38.0  <span style="color: #555555;">2024-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pheatmap     * 1.0.12  <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pillar         1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgconfig      2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgdown        2.1.1   <span style="color: #555555;">2024-09-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  prettyunits    1.2.0   <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  progress       1.2.3   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  purrr          1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  R6             2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ragg           1.3.3   <span style="color: #555555;">2024-09-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rappdirs       0.3.3   <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RColorBrewer   1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rcpp           1.0.13  <span style="color: #555555;">2024-07-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readr          2.1.5   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readxl         1.4.3   <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rlang          1.1.4   <span style="color: #555555;">2024-06-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rmarkdown      2.28    <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rvest          1.0.4   <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sass           0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scales         1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  selectr        0.4-2   <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sessioninfo    1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringi        1.8.4   <span style="color: #555555;">2024-05-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringr        1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  systemfonts    1.1.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  textshaping    0.4.0   <span style="color: #555555;">2024-05-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tibble       * 3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyr        * 1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyselect     1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  timechange     0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tzdb           0.4.0   <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  utf8           1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vctrs          0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vroom          1.6.5   <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  withr          3.0.1   <span style="color: #555555;">2024-07-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xfun           0.48    <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xml2           1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  yaml           2.3.10  <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [1] /usr/local/lib/R/site-library</span></span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [2] /usr/local/lib/R/library</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span></code></pre>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
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-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
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 </div>
 
-  
 
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+
 
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 </html>
diff --git a/articles/pw_bk_files/figure-html/barplot-1.png b/articles/pw_bk_files/figure-html/barplot-1.png
index 0877a813..8687cbd6 100644
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diff --git a/articles/pw_bk_files/figure-html/heatmap-1.png b/articles/pw_bk_files/figure-html/heatmap-1.png
index 77a8ffd5..e8639527 100644
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diff --git a/articles/pw_bk_files/figure-html/targets-1.png b/articles/pw_bk_files/figure-html/targets-1.png
index c1239921..2c0f7a4d 100644
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diff --git a/articles/pw_sc.html b/articles/pw_sc.html
index 45cd7509..a3a2a219 100644
--- a/articles/pw_sc.html
+++ b/articles/pw_sc.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="decoupleR">
 <title>Pathway activity inference from scRNA-seq • decoupleR</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -15,16 +14,11 @@
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 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <meta property="og:title" content="Pathway activity inference from scRNA-seq">
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-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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@@ -34,67 +28,42 @@
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-    
 
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     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
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+<li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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+<ul class="navbar-nav">
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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+
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 </nav><div class="container template-article">
 
@@ -107,7 +76,7 @@
                         <h4 data-toc-skip class="author">Pau
 Badia-i-Mompel</h4>
             <address class="author_afil">
-      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/vignettes/pw_sc.Rmd" class="external-link"><code>vignettes/pw_sc.Rmd</code></a></small>
+      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/vignettes/pw_sc.Rmd" class="external-link"><code>vignettes/pw_sc.Rmd</code></a></small>
       <div class="d-none name"><code>pw_sc.Rmd</code></div>
     </address>
 </div>
@@ -152,7 +121,12 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/file.path.html" class="external-link">file.path</a></span><span class="op">(</span><span class="va">inputs_dir</span>, <span class="st">"sc_data.rds"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <p>We can observe that we have different cell types:</p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, reduction <span class="op">=</span> <span class="st">"umap"</span>, label <span class="op">=</span> <span class="cn">TRUE</span>, pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="va">p</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, </span>
+<span>                     reduction <span class="op">=</span> <span class="st">"umap"</span>, </span>
+<span>                     label <span class="op">=</span> <span class="cn">TRUE</span>, </span>
+<span>                     pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>     <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="va">p</span></span></code></pre></div>
 <p><img src="pw_sc_files/figure-html/umap-1.png" width="700"></p>
 <div class="section level4">
 <h4 id="progeny-model">PROGENy model<a class="anchor" aria-label="anchor" href="#progeny-model"></a>
@@ -207,7 +181,7 @@ <h4 id="progeny-model">PROGENy model<a class="anchor" aria-label="anchor" href="
 </ul>
 <p>To access it we can use <code>decoupleR</code>:</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/get_progeny.html">get_progeny</a></span><span class="op">(</span>organism <span class="op">=</span> <span class="st">'human'</span>, top <span class="op">=</span> <span class="fl">500</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/get_progeny.html">get_progeny</a></span><span class="op">(</span>organism <span class="op">=</span> <span class="st">'human'</span>, top <span class="op">=</span> <span class="fl">500</span><span class="op">)</span></span>
 <span><span class="va">net</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 7,000 × 4</span></span></span>
 <span><span class="co">#&gt;    source   target  weight  p_value</span></span>
@@ -247,8 +221,12 @@ <h2 id="activity-inference-with-multivariate-linear-model-mlm">Activity inferenc
 <span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">RNA</span><span class="op">@</span><span class="va">data</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Run mlm</span></span>
-<span><span class="va">acts</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_mlm.html">run_mlm</a></span><span class="op">(</span>mat<span class="op">=</span><span class="va">mat</span>, net<span class="op">=</span><span class="va">net</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                .mor<span class="op">=</span><span class="st">'weight'</span>, minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span><span class="va">acts</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_mlm.html">run_mlm</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat</span>, </span>
+<span>                           net <span class="op">=</span> <span class="va">net</span>, </span>
+<span>                           .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                           .target <span class="op">=</span> <span class="st">'target'</span>,</span>
+<span>                           .mor <span class="op">=</span> <span class="st">'weight'</span>, </span>
+<span>                           minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
 <span><span class="va">acts</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,240 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source   condition         score  p_value</span></span>
@@ -274,27 +252,37 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Extract mlm and store it in pathwaysmlm in data</span></span>
 <span><span class="va">data</span><span class="op">[[</span><span class="st">'pathwaysmlm'</span><span class="op">]</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="va">acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'source'</span>, names_from <span class="op">=</span> <span class="st">'condition'</span>,</span>
-<span>              values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'source'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/CreateAssayObject.html" class="external-link">CreateAssayObject</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span></span>
+<span>                         <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                            names_from <span class="op">=</span> <span class="st">'condition'</span>,</span>
+<span>                                            values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                         <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">'source'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                         <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/CreateAssayObject.html" class="external-link">CreateAssayObject</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Change assay</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"pathwaysmlm"</span></span>
+<span><span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"pathwaysmlm"</span></span>
 <span></span>
 <span><span class="co"># Scale the data</span></span>
-<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/ScaleData.html" class="external-link">ScaleData</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
+<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/ScaleData.html" class="external-link">ScaleData</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
 <span><span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">pathwaysmlm</span><span class="op">@</span><span class="va">data</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">pathwaysmlm</span><span class="op">@</span><span class="va">scale.data</span></span></code></pre></div>
 <p>This new assay can be used to plot activities. Here we visualize the
 Trail pathway, associated with apoptosis, which seems that in B and NK
 cells is more active.</p>
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">p1</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, reduction <span class="op">=</span> <span class="st">"umap"</span>, label <span class="op">=</span> <span class="cn">TRUE</span>, pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'Cell types'</span><span class="op">)</span></span>
-<span><span class="va">p2</span> <span class="op">&lt;-</span> <span class="op">(</span><span class="fu"><a href="https://satijalab.org/seurat/reference/FeaturePlot.html" class="external-link">FeaturePlot</a></span><span class="op">(</span><span class="va">data</span>, features <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Trail"</span><span class="op">)</span><span class="op">)</span> <span class="op">&amp;</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_gradient.html" class="external-link">scale_colour_gradient2</a></span><span class="op">(</span>low <span class="op">=</span> <span class="st">'blue'</span>, mid <span class="op">=</span> <span class="st">'white'</span>, high <span class="op">=</span> <span class="st">'red'</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'Trail activity'</span><span class="op">)</span></span>
-<span><span class="va">p1</span> <span class="op">|</span> <span class="va">p2</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="va">p1</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, </span>
+<span>                      reduction <span class="op">=</span> <span class="st">"umap"</span>, </span>
+<span>                      label <span class="op">=</span> <span class="cn">TRUE</span>, </span>
+<span>                      pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'Cell types'</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">2</span>, <span class="fl">10</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p2</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/FeaturePlot.html" class="external-link">FeaturePlot</a></span><span class="op">(</span><span class="va">data</span>, features <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Trail"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_gradient.html" class="external-link">scale_colour_gradient2</a></span><span class="op">(</span>low <span class="op">=</span> <span class="va">colors</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span>, mid <span class="op">=</span> <span class="st">'white'</span>, high <span class="op">=</span> <span class="va">colors</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span><span class="op">)</span> <span class="op">+</span></span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'Trail activity'</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p</span> <span class="op">&lt;-</span> <span class="va">p1</span> <span class="op">|</span> <span class="va">p2</span></span>
+<span><span class="va">p</span></span></code></pre></div>
 <p><img src="pw_sc_files/figure-html/projected_acts-1.png" width="768"></p>
 </div>
 <div class="section level2">
@@ -305,28 +293,38 @@ <h2 id="exploration">Exploration<a class="anchor" aria-label="anchor" href="#exp
 <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Extract activities from object as a long dataframe</span></span>
 <span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/t.html" class="external-link">t</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">pathwaysmlm</span><span class="op">@</span><span class="va">data</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>cluster <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/Idents.html" class="external-link">Idents</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">pivot_longer</a></span><span class="op">(</span>cols <span class="op">=</span> <span class="op">-</span><span class="va">cluster</span>, names_to <span class="op">=</span> <span class="st">"source"</span>, values_to <span class="op">=</span> <span class="st">"score"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">cluster</span>, <span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>mean <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span></span>
+<span>      <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>cluster <span class="op">=</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/Idents.html" class="external-link">Idents</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">pivot_longer</a></span><span class="op">(</span>cols <span class="op">=</span> <span class="op">-</span><span class="va">cluster</span>, </span>
+<span>                          names_to <span class="op">=</span> <span class="st">"source"</span>, </span>
+<span>                          values_to <span class="op">=</span> <span class="st">"score"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">cluster</span>, <span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>mean <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Transform to wide matrix</span></span>
 <span><span class="va">top_acts_mat</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'cluster'</span>, names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
-<span>              values_from <span class="op">=</span> <span class="st">'mean'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'cluster'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>                <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'cluster'</span>, </span>
+<span>                                   names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
+<span>                                   values_from <span class="op">=</span> <span class="st">'mean'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">'cluster'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># Choose color palette</span></span>
-<span><span class="va">palette_length</span> <span class="op">=</span> <span class="fl">100</span></span>
-<span><span class="va">my_color</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Darkblue"</span>, <span class="st">"white"</span>,<span class="st">"red"</span><span class="op">)</span><span class="op">)</span><span class="op">(</span><span class="va">palette_length</span><span class="op">)</span></span>
+<span><span class="co"># Color scale</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">2</span>, <span class="fl">0</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
-<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">2</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">1.25</span>, <span class="fl">0</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
+<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">1.25</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Plot</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">top_acts_mat</span>, border_color <span class="op">=</span> <span class="cn">NA</span>, color<span class="op">=</span><span class="va">my_color</span>, breaks <span class="op">=</span> <span class="va">my_breaks</span><span class="op">)</span> </span></code></pre></div>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">top_acts_mat</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   breaks <span class="op">=</span> <span class="va">my_breaks</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">20</span><span class="op">)</span> </span></code></pre></div>
 <p><img src="pw_sc_files/figure-html/mean_acts-1.png" width="700"></p>
 <p>In this specific example, we can observe that Trail is more active in
 B and NK cells.</p>
@@ -336,197 +334,195 @@ <h2 id="session-information">Session information<a class="anchor" aria-label="an
 </h2>
 <pre><code><span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
 <span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">setting </span> <span style="color: #555555; font-style: italic;">value</span></span></span>
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-<span><span class="co">#&gt;  os       Ubuntu 22.04.4 LTS</span></span>
+<span><span class="co">#&gt;  version  R version 4.4.1 (2024-06-14)</span></span>
+<span><span class="co">#&gt;  os       Ubuntu 22.04.5 LTS</span></span>
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 <span><span class="co">#&gt;  language en</span></span>
 <span><span class="co">#&gt;  collate  en_US.UTF-8</span></span>
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 <span><span class="co">#&gt;  tz       UTC</span></span>
-<span><span class="co">#&gt;  date     2024-04-11</span></span>
-<span><span class="co">#&gt;  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown)</span></span>
+<span><span class="co">#&gt;  date     2024-10-19</span></span>
+<span><span class="co">#&gt;  pandoc   3.4 @ /usr/bin/ (via rmarkdown)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
-<span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">package         </span> <span style="color: #555555; font-style: italic;">*</span> <span style="color: #555555; font-style: italic;">version </span> <span style="color: #555555; font-style: italic;">date (UTC)</span> <span style="color: #555555; font-style: italic;">lib</span> <span style="color: #555555; font-style: italic;">source</span></span></span>
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-<span><span class="co">#&gt;  gridExtra          2.3      <span style="color: #555555;">2017-09-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  highr              0.10     <span style="color: #555555;">2022-12-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  hms                1.1.3    <span style="color: #555555;">2023-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  ica                1.0-3    <span style="color: #555555;">2022-07-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  igraph             2.0.3    <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  irlba              2.3.5.1  <span style="color: #555555;">2022-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  jquerylib          0.1.4    <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  jsonlite           1.8.8    <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  KernSmooth         2.23-22  <span style="color: #555555;">2023-07-10</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  knitr              1.46     <span style="color: #555555;">2024-04-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  labeling           0.4.3    <span style="color: #555555;">2023-08-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  later              1.3.2    <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lattice            0.22-6   <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lazyeval           0.2.2    <span style="color: #555555;">2019-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  leiden             0.4.3.1  <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lifecycle          1.0.4    <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  listenv            0.9.1    <span style="color: #555555;">2024-01-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lmtest             0.9-40   <span style="color: #555555;">2022-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  logger             0.3.0    <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lubridate          1.9.3    <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  magrittr           2.0.3    <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  MASS               7.3-60.2 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[2]</span> <span style="color: #BB00BB; font-weight: bold;">local</span></span></span>
-<span><span class="co">#&gt;  Matrix             1.7-0    <span style="color: #555555;">2024-03-22</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  matrixStats        1.3.0    <span style="color: #555555;">2024-04-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  memoise            2.0.1    <span style="color: #555555;">2021-11-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  mime               0.12     <span style="color: #555555;">2021-09-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  miniUI             0.1.1.1  <span style="color: #555555;">2018-05-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  munsell            0.5.1    <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  nlme               3.1-164  <span style="color: #555555;">2023-11-27</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  OmnipathR          3.11.10  <span style="color: #555555;">2024-03-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
-<span><span class="co">#&gt;  parallelly         1.37.1   <span style="color: #555555;">2024-02-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  patchwork        * 1.2.0    <span style="color: #555555;">2024-01-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pbapply            1.7-2    <span style="color: #555555;">2023-06-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pheatmap         * 1.0.12   <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pillar             1.9.0    <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgconfig          2.0.3    <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgdown            2.0.8    <span style="color: #555555;">2024-04-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  plotly             4.10.4   <span style="color: #555555;">2024-01-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  plyr               1.8.9    <span style="color: #555555;">2023-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  png                0.1-8    <span style="color: #555555;">2022-11-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  polyclip           1.10-6   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  prettyunits        1.2.0    <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  progress           1.2.3    <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  progressr          0.14.0   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  promises           1.3.0    <span style="color: #555555;">2024-04-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  purrr              1.0.2    <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  R6                 2.5.1    <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ragg               1.3.0    <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RANN               2.6.1    <span style="color: #555555;">2019-01-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rappdirs           0.3.3    <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RColorBrewer       1.1-3    <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Rcpp               1.0.12   <span style="color: #555555;">2024-01-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RcppAnnoy          0.0.22   <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RcppHNSW           0.6.0    <span style="color: #555555;">2024-02-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readr              2.1.5    <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readxl             1.4.3    <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  reshape2           1.4.4    <span style="color: #555555;">2020-04-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  reticulate         1.35.0   <span style="color: #555555;">2024-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rlang              1.1.3    <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rmarkdown          2.26     <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ROCR               1.0-11   <span style="color: #555555;">2020-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RSpectra           0.16-1   <span style="color: #555555;">2022-04-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Rtsne              0.17     <span style="color: #555555;">2023-12-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rvest              1.0.4    <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sass               0.4.9    <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  scales             1.3.0    <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  scattermore        1.2      <span style="color: #555555;">2023-06-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sctransform        0.4.1    <span style="color: #555555;">2023-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  selectr            0.4-2    <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sessioninfo        1.2.2    <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Seurat           * 5.0.3    <span style="color: #555555;">2024-03-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  SeuratObject     * 5.0.1    <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  shiny              1.8.1.1  <span style="color: #555555;">2024-04-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sp               * 2.1-3    <span style="color: #555555;">2024-01-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spam               2.10-0   <span style="color: #555555;">2023-10-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.data      3.0-4    <span style="color: #555555;">2024-01-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.explore   3.2-7    <span style="color: #555555;">2024-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.geom      3.2-9    <span style="color: #555555;">2024-02-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.random    3.2-3    <span style="color: #555555;">2024-02-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.sparse    3.0-3    <span style="color: #555555;">2023-10-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.utils     3.0-4    <span style="color: #555555;">2023-10-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringi            1.8.3    <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringr            1.5.1    <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  survival           3.5-8    <span style="color: #555555;">2024-02-14</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  systemfonts        1.0.6    <span style="color: #555555;">2024-03-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tensor             1.5      <span style="color: #555555;">2012-05-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  textshaping        0.3.7    <span style="color: #555555;">2023-10-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tibble           * 3.2.1    <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyr            * 1.3.1    <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyselect         1.2.1    <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  timechange         0.3.0    <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tzdb               0.4.0    <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  utf8               1.2.4    <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  uwot               0.1.16   <span style="color: #555555;">2023-06-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vctrs              0.6.5    <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  viridisLite        0.4.2    <span style="color: #555555;">2023-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vroom              1.6.5    <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  withr              3.0.0    <span style="color: #555555;">2024-01-16</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xfun               0.43     <span style="color: #555555;">2024-03-25</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xml2               1.3.6    <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xtable             1.8-4    <span style="color: #555555;">2019-04-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  yaml               2.3.8    <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  zoo                1.8-12   <span style="color: #555555;">2023-04-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
+<span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">package         </span> <span style="color: #555555; font-style: italic;">*</span> <span style="color: #555555; font-style: italic;">version</span> <span style="color: #555555; font-style: italic;">date (UTC)</span> <span style="color: #555555; font-style: italic;">lib</span> <span style="color: #555555; font-style: italic;">source</span></span></span>
+<span><span class="co">#&gt;  abind              1.4-8   <span style="color: #555555;">2024-09-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  backports          1.5.0   <span style="color: #555555;">2024-05-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocManager        1.30.25 <span style="color: #555555;">2024-08-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocParallel       1.38.0  <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  BiocStyle        * 2.32.1  <span style="color: #555555;">2024-06-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  bit                4.5.0   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bit64              4.5.2   <span style="color: #555555;">2024-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bookdown           0.41    <span style="color: #555555;">2024-10-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bslib              0.8.0   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cachem             1.1.0   <span style="color: #555555;">2024-05-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cellranger         1.1.0   <span style="color: #555555;">2016-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  checkmate          2.3.2   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cli                3.6.3   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cluster            2.1.6   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  codetools          0.2-20  <span style="color: #555555;">2024-03-31</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  colorspace         2.1-1   <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cowplot            1.1.3   <span style="color: #555555;">2024-01-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  crayon             1.5.3   <span style="color: #555555;">2024-06-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  curl               5.2.3   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  data.table         1.16.2  <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  decoupleR        * 2.9.7   <span style="color: #555555;">2024-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">Bioconductor</span></span></span>
+<span><span class="co">#&gt;  deldir             2.0-4   <span style="color: #555555;">2024-02-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  desc               1.4.3   <span style="color: #555555;">2023-12-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  digest             0.6.37  <span style="color: #555555;">2024-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dotCall64          1.2     <span style="color: #555555;">2024-10-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dplyr            * 1.1.4   <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  evaluate           1.0.1   <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fansi              1.0.6   <span style="color: #555555;">2023-12-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  farver             2.1.2   <span style="color: #555555;">2024-05-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastDummies        1.7.4   <span style="color: #555555;">2024-08-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastmap            1.2.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fitdistrplus       1.2-1   <span style="color: #555555;">2024-07-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fs                 1.6.4   <span style="color: #555555;">2024-04-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  future             1.34.0  <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  future.apply       1.11.2  <span style="color: #555555;">2024-03-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  generics           0.1.3   <span style="color: #555555;">2022-07-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggplot2          * 3.5.1   <span style="color: #555555;">2024-04-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggrepel            0.9.6   <span style="color: #555555;">2024-09-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggridges           0.5.6   <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  globals            0.16.3  <span style="color: #555555;">2024-03-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  glue               1.8.0   <span style="color: #555555;">2024-09-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  goftest            1.2-3   <span style="color: #555555;">2021-10-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gridExtra          2.3     <span style="color: #555555;">2017-09-09</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gtable             0.3.5   <span style="color: #555555;">2024-04-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  highr              0.11    <span style="color: #555555;">2024-05-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  hms                1.1.3   <span style="color: #555555;">2023-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmltools          0.5.8.1 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmlwidgets        1.6.4   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httpuv             1.6.15  <span style="color: #555555;">2024-03-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httr               1.4.7   <span style="color: #555555;">2023-08-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ica                1.0-3   <span style="color: #555555;">2022-07-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  igraph             2.0.3   <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  irlba              2.3.5.1 <span style="color: #555555;">2022-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jquerylib          0.1.4   <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jsonlite           1.8.9   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  KernSmooth         2.23-24 <span style="color: #555555;">2024-05-17</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  knitr              1.48    <span style="color: #555555;">2024-07-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  labeling           0.4.3   <span style="color: #555555;">2023-08-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  later              1.3.2   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lattice            0.22-6  <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  lazyeval           0.2.2   <span style="color: #555555;">2019-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  leiden             0.4.3.1 <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lifecycle          1.0.4   <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  listenv            0.9.1   <span style="color: #555555;">2024-01-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lmtest             0.9-40  <span style="color: #555555;">2022-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  logger             0.3.0   <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lubridate          1.9.3   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  magrittr           2.0.3   <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  MASS               7.3-61  <span style="color: #555555;">2024-06-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  Matrix             1.7-1   <span style="color: #555555;">2024-10-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  matrixStats        1.4.1   <span style="color: #555555;">2024-09-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  mime               0.12    <span style="color: #555555;">2021-09-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  miniUI             0.1.1.1 <span style="color: #555555;">2018-05-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  munsell            0.5.1   <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  nlme               3.1-166 <span style="color: #555555;">2024-08-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  OmnipathR          3.12.4  <span style="color: #555555;">2024-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  parallelly         1.38.0  <span style="color: #555555;">2024-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  patchwork        * 1.3.0   <span style="color: #555555;">2024-09-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pbapply            1.7-2   <span style="color: #555555;">2023-06-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pheatmap         * 1.0.12  <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pillar             1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgconfig          2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgdown            2.1.1   <span style="color: #555555;">2024-09-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  plotly             4.10.4  <span style="color: #555555;">2024-01-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  plyr               1.8.9   <span style="color: #555555;">2023-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  png                0.1-8   <span style="color: #555555;">2022-11-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  polyclip           1.10-7  <span style="color: #555555;">2024-07-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  prettyunits        1.2.0   <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  progress           1.2.3   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  progressr          0.14.0  <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  promises           1.3.0   <span style="color: #555555;">2024-04-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  purrr              1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  R6                 2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ragg               1.3.3   <span style="color: #555555;">2024-09-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RANN               2.6.2   <span style="color: #555555;">2024-08-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rappdirs           0.3.3   <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RColorBrewer       1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rcpp               1.0.13  <span style="color: #555555;">2024-07-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RcppAnnoy          0.0.22  <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RcppHNSW           0.6.0   <span style="color: #555555;">2024-02-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readr              2.1.5   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readxl             1.4.3   <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  reshape2           1.4.4   <span style="color: #555555;">2020-04-09</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  reticulate         1.39.0  <span style="color: #555555;">2024-09-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rlang              1.1.4   <span style="color: #555555;">2024-06-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rmarkdown          2.28    <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ROCR               1.0-11  <span style="color: #555555;">2020-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RSpectra           0.16-2  <span style="color: #555555;">2024-07-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rtsne              0.17    <span style="color: #555555;">2023-12-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rvest              1.0.4   <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sass               0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scales             1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scattermore        1.2     <span style="color: #555555;">2023-06-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sctransform        0.4.1   <span style="color: #555555;">2023-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  selectr            0.4-2   <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sessioninfo        1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Seurat           * 5.1.0   <span style="color: #555555;">2024-05-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  SeuratObject     * 5.0.2   <span style="color: #555555;">2024-05-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  shiny              1.9.1   <span style="color: #555555;">2024-08-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sp               * 2.1-4   <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spam               2.11-0  <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.data      3.1-2   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.explore   3.3-2   <span style="color: #555555;">2024-08-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.geom      3.3-3   <span style="color: #555555;">2024-09-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.random    3.3-2   <span style="color: #555555;">2024-09-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.sparse    3.1-0   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.univar    3.0-1   <span style="color: #555555;">2024-09-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.utils     3.1-0   <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringi            1.8.4   <span style="color: #555555;">2024-05-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringr            1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  survival           3.7-0   <span style="color: #555555;">2024-06-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  systemfonts        1.1.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tensor             1.5     <span style="color: #555555;">2012-05-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  textshaping        0.4.0   <span style="color: #555555;">2024-05-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tibble           * 3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyr            * 1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyselect         1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  timechange         0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tzdb               0.4.0   <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  utf8               1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  uwot               0.2.2   <span style="color: #555555;">2024-04-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vctrs              0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  viridisLite        0.4.2   <span style="color: #555555;">2023-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vroom              1.6.5   <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  withr              3.0.1   <span style="color: #555555;">2024-07-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xfun               0.48    <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xml2               1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xtable             1.8-4   <span style="color: #555555;">2019-04-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  yaml               2.3.10  <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  zoo                1.8-12  <span style="color: #555555;">2023-04-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [1] /usr/local/lib/R/site-library</span></span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [2] /usr/local/lib/R/library</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span></code></pre>
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diff --git a/articles/pw_sc_files/figure-html/mean_acts-1.png b/articles/pw_sc_files/figure-html/mean_acts-1.png
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diff --git a/articles/pw_sc_files/figure-html/projected_acts-1.png b/articles/pw_sc_files/figure-html/projected_acts-1.png
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diff --git a/articles/tf_bk.html b/articles/tf_bk.html
index 33b091c8..d9fb9909 100644
--- a/articles/tf_bk.html
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@@ -5,7 +5,6 @@
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+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
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-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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@@ -34,67 +28,42 @@
 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+<li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
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-  <a class="nav-link" href="../news/index.html">Changelog</a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
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-  <a class="external-link nav-link" href="https://twitter.com/saezlab">
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-  <a class="external-link nav-link" href="https://www.saezlab.org">
-    <span class="fas fa fas fa-university"></span>
-     
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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       </ul>
 </div>
 
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 </nav><div class="container template-article">
 
@@ -107,7 +76,7 @@
                         <h4 data-toc-skip class="author">Pau
 Badia-i-Mompel</h4>
             <address class="author_afil">
-      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/vignettes/tf_bk.Rmd" class="external-link"><code>vignettes/tf_bk.Rmd</code></a></small>
+      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/vignettes/tf_bk.Rmd" class="external-link"><code>vignettes/tf_bk.Rmd</code></a></small>
       <div class="d-none name"><code>tf_bk.Rmd</code></div>
     </address>
 </div>
@@ -163,9 +132,11 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Remove NAs and set row names</span></span>
 <span><span class="va">counts</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">counts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span><span class="op">)</span>, <span class="op">~</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/if_else.html" class="external-link">if_else</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span>,<span class="fl">0</span>,<span class="va">.x</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"gene"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>          <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span><span class="op">)</span>, </span>
+<span>                           <span class="op">~</span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/if_else.html" class="external-link">if_else</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span>, <span class="fl">0</span>, <span class="va">.x</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>          <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"gene"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>          <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">counts</span><span class="op">)</span></span>
 <span><span class="co">#&gt;          PANC1.WT.Rep1 PANC1.WT.Rep2 PANC1.WT.Rep3 PANC1.FOXA2KO.Rep1</span></span>
 <span><span class="co">#&gt; NOC2L        10.052588     11.949123     12.057774          12.312291</span></span>
@@ -184,6 +155,7 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <p>The design meta-data:</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">design</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">design</span></span>
+<span></span>
 <span><span class="va">design</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 2</span></span></span>
 <span><span class="co">#&gt;   sample             condition    </span></span>
@@ -199,10 +171,11 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Extract t-values per gene</span></span>
 <span><span class="va">deg</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">limma_ttop</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">ID</span>, <span class="va">logFC</span>, <span class="va">t</span>, <span class="va">P.Value</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">t</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
-<span>    <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"ID"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">ID</span>, <span class="va">logFC</span>, <span class="va">t</span>, <span class="va">P.Value</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">t</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span> </span>
+<span>       <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span>var <span class="op">=</span> <span class="st">"ID"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">deg</span><span class="op">)</span></span>
 <span><span class="co">#&gt;             logFC          t      P.Value</span></span>
 <span><span class="co">#&gt; RHBDL2  -1.823940 -12.810588 3.030276e-06</span></span>
@@ -230,7 +203,9 @@ <h2 id="collectri-network">CollecTRI network<a class="anchor" aria-label="anchor
 complexes or splits them into subunits, by default we recommend to keep
 complexes together.</p>
 <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/get_collectri.html">get_collectri</a></span><span class="op">(</span>organism<span class="op">=</span><span class="st">'human'</span>, split_complexes<span class="op">=</span><span class="cn">FALSE</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/get_collectri.html">get_collectri</a></span><span class="op">(</span>organism <span class="op">=</span> <span class="st">'human'</span>, </span>
+<span>                                split_complexes <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">net</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 43,178 × 3</span></span></span>
 <span><span class="co">#&gt;    source target   mor</span></span>
@@ -267,8 +242,13 @@ <h2 id="activity-inference-with-univariate-linear-model-ulm">Activity inference
 use.</p>
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Run ulm</span></span>
-<span><span class="va">sample_acts</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat<span class="op">=</span><span class="va">counts</span>, net<span class="op">=</span><span class="va">net</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                  .mor<span class="op">=</span><span class="st">'mor'</span>, minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span><span class="va">sample_acts</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">counts</span>, </span>
+<span>                                  net <span class="op">=</span> <span class="va">net</span>, </span>
+<span>                                  .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                  .target <span class="op">=</span> <span class="st">'target'</span>,</span>
+<span>                                  .mor <span class="op">=</span> <span class="st">'mor'</span>, </span>
+<span>                                  minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">sample_acts</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 3,480 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source condition           score p_value</span></span>
@@ -295,39 +275,53 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 <span></span>
 <span><span class="co"># Transform to wide matrix</span></span>
 <span><span class="va">sample_acts_mat</span> <span class="op">&lt;-</span> <span class="va">sample_acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'condition'</span>, names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
-<span>              values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'condition'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>                   <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'condition'</span>, </span>
+<span>                                      names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
+<span>                                      values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                   <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'condition'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                   <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Get top tfs with more variable means across clusters</span></span>
 <span><span class="va">tfs</span> <span class="op">&lt;-</span> <span class="va">sample_acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>std <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="op">-</span><span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs</a></span><span class="op">(</span><span class="va">std</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">n_tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>std <span class="op">=</span> <span class="fu">stats</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="op">-</span><span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs</a></span><span class="op">(</span><span class="va">std</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">n_tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">sample_acts_mat</span> <span class="op">&lt;-</span> <span class="va">sample_acts_mat</span><span class="op">[</span>,<span class="va">tfs</span><span class="op">]</span></span>
 <span></span>
 <span><span class="co"># Scale per sample</span></span>
 <span><span class="va">sample_acts_mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/scale.html" class="external-link">scale</a></span><span class="op">(</span><span class="va">sample_acts_mat</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Choose color palette</span></span>
-<span><span class="va">palette_length</span> <span class="op">=</span> <span class="fl">100</span></span>
-<span><span class="va">my_color</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Darkblue"</span>, <span class="st">"white"</span>,<span class="st">"red"</span><span class="op">)</span><span class="op">)</span><span class="op">(</span><span class="va">palette_length</span><span class="op">)</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">3</span>, <span class="fl">0</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
-<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">3</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">2</span>, <span class="fl">0</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
+<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">2</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Plot</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">sample_acts_mat</span>, border_color <span class="op">=</span> <span class="cn">NA</span>, color<span class="op">=</span><span class="va">my_color</span>, breaks <span class="op">=</span> <span class="va">my_breaks</span><span class="op">)</span> </span></code></pre></div>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">sample_acts_mat</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   breaks <span class="op">=</span> <span class="va">my_breaks</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">15</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">15</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">20</span><span class="op">)</span></span></code></pre></div>
 <p><img src="tf_bk_files/figure-html/heatmap-1.png" width="700"></p>
 <p>We can also infer TF activities from the t-values of the DEGs between
 KO and WT:</p>
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Run ulm</span></span>
-<span><span class="va">contrast_acts</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat<span class="op">=</span><span class="va">deg</span><span class="op">[</span>, <span class="st">'t'</span>, drop<span class="op">=</span><span class="cn">FALSE</span><span class="op">]</span>, net<span class="op">=</span><span class="va">net</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                  .mor<span class="op">=</span><span class="st">'mor'</span>, minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span><span class="va">contrast_acts</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">deg</span><span class="op">[</span>, <span class="st">'t'</span>, drop <span class="op">=</span> <span class="cn">FALSE</span><span class="op">]</span>, </span>
+<span>                                    net <span class="op">=</span> <span class="va">net</span>, </span>
+<span>                                    .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                    .target <span class="op">=</span> <span class="st">'target'</span>,</span>
+<span>                                    .mor<span class="op">=</span><span class="st">'mor'</span>, </span>
+<span>                                    minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">contrast_acts</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 580 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source condition   score p_value</span></span>
@@ -348,30 +342,46 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 <code class="sourceCode R"><span></span>
 <span><span class="co"># Filter top TFs in both signs</span></span>
 <span><span class="va">f_contrast_acts</span> <span class="op">&lt;-</span> <span class="va">contrast_acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>rnk <span class="op">=</span> <span class="cn">NA</span><span class="op">)</span></span>
+<span>                   <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>rnk <span class="op">=</span> <span class="cn">NA</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">msk</span> <span class="op">&lt;-</span> <span class="va">f_contrast_acts</span><span class="op">$</span><span class="va">score</span> <span class="op">&gt;</span> <span class="fl">0</span></span>
+<span></span>
 <span><span class="va">f_contrast_acts</span><span class="op">[</span><span class="va">msk</span>, <span class="st">'rnk'</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rank.html" class="external-link">rank</a></span><span class="op">(</span><span class="op">-</span><span class="va">f_contrast_acts</span><span class="op">[</span><span class="va">msk</span>, <span class="st">'score'</span><span class="op">]</span><span class="op">)</span></span>
 <span><span class="va">f_contrast_acts</span><span class="op">[</span><span class="op">!</span><span class="va">msk</span>, <span class="st">'rnk'</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rank.html" class="external-link">rank</a></span><span class="op">(</span><span class="op">-</span><span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs</a></span><span class="op">(</span><span class="va">f_contrast_acts</span><span class="op">[</span><span class="op">!</span><span class="va">msk</span>, <span class="st">'score'</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">tfs</span> <span class="op">&lt;-</span> <span class="va">f_contrast_acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">rnk</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">n_tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">rnk</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">n_tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">f_contrast_acts</span> <span class="op">&lt;-</span> <span class="va">f_contrast_acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">source</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">tfs</span><span class="op">)</span></span>
+<span>                   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">source</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">tfs</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># Plot</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">f_contrast_acts</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/reorder.factor.html" class="external-link">reorder</a></span><span class="op">(</span><span class="va">source</span>, <span class="va">score</span><span class="op">)</span>, y <span class="op">=</span> <span class="va">score</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_bar</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>fill <span class="op">=</span> <span class="va">score</span><span class="op">)</span>, stat <span class="op">=</span> <span class="st">"identity"</span><span class="op">)</span> <span class="op">+</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_gradient.html" class="external-link">scale_fill_gradient2</a></span><span class="op">(</span>low <span class="op">=</span> <span class="st">"darkblue"</span>, high <span class="op">=</span> <span class="st">"indianred"</span>, </span>
-<span>        mid <span class="op">=</span> <span class="st">"whitesmoke"</span>, midpoint <span class="op">=</span> <span class="fl">0</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>axis.title <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>face <span class="op">=</span> <span class="st">"bold"</span>, size <span class="op">=</span> <span class="fl">12</span><span class="op">)</span>,</span>
-<span>        axis.text.x <span class="op">=</span> </span>
-<span>            <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>angle <span class="op">=</span> <span class="fl">45</span>, hjust <span class="op">=</span> <span class="fl">1</span>, size <span class="op">=</span><span class="fl">10</span>, face<span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>,</span>
-<span>        axis.text.y <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>size <span class="op">=</span><span class="fl">10</span>, face<span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>,</span>
-<span>        panel.grid.major <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_blank</a></span><span class="op">(</span><span class="op">)</span>, </span>
-<span>        panel.grid.minor <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_blank</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">xlab</a></span><span class="op">(</span><span class="st">"TFs"</span><span class="op">)</span></span></code></pre></div>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">2</span>, <span class="fl">10</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p</span> <span class="op">&lt;-</span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">f_contrast_acts</span>, </span>
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+<span>                                            y <span class="op">=</span> <span class="va">score</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
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+<span>                       color <span class="op">=</span> <span class="st">"black"</span>,</span>
+<span>                       stat <span class="op">=</span> <span class="st">"identity"</span><span class="op">)</span> <span class="op">+</span></span>
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+<span>                                   mid <span class="op">=</span> <span class="st">"whitesmoke"</span>, </span>
+<span>                                   high <span class="op">=</span> <span class="va">colors</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span>, </span>
+<span>                                   midpoint <span class="op">=</span> <span class="fl">0</span><span class="op">)</span> <span class="op">+</span> </span>
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+<span>                                                  hjust <span class="op">=</span> <span class="fl">1</span>, </span>
+<span>                                                  size <span class="op">=</span> <span class="fl">10</span>, </span>
+<span>                                                  face <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>,</span>
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+<span>                                                  face <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>,</span>
+<span>              panel.grid.major <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_blank</a></span><span class="op">(</span><span class="op">)</span>, </span>
+<span>              panel.grid.minor <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_blank</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">xlab</a></span><span class="op">(</span><span class="st">"TFs"</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p</span></span></code></pre></div>
 <p><img src="tf_bk_files/figure-html/barplot-1.png" width="700"></p>
 <p>The TFs GLI3 and SPDEF are deactivated in KO when compared to WT,
 while MUC and NFKB1 seem to be activated.</p>
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+<span>                                            size <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs</a></span><span class="op">(</span><span class="va">mor</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">2.5</span>, </span>
+<span>                         color <span class="op">=</span> <span class="st">"black"</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">1.5</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_manual.html" class="external-link">scale_colour_manual</a></span><span class="op">(</span>values <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">colors</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span>, <span class="va">colors</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span>, <span class="st">"grey"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggrepel</span><span class="fu">::</span><span class="fu"><a href="https://ggrepel.slowkow.com/reference/geom_text_repel.html" class="external-link">geom_label_repel</a></span><span class="op">(</span>mapping <span class="op">=</span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>label <span class="op">=</span> <span class="va">ID</span>,</span>
+<span>                                                      size <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">"none"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span>xintercept <span class="op">=</span> <span class="fl">0</span>, linetype <span class="op">=</span> <span class="st">'dotted'</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_hline</a></span><span class="op">(</span>yintercept <span class="op">=</span> <span class="fl">0</span>, linetype <span class="op">=</span> <span class="st">'dotted'</span><span class="op">)</span> <span class="op">+</span></span>
+<span>     <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="va">tf</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p</span></span></code></pre></div>
 <p><img src="tf_bk_files/figure-html/targets-1.png" width="700"></p>
 <p>Here blue means that the sign of multiplying the <code>mor</code> and
 <code>t-value</code> is negative, meaning that these genes are
@@ -416,135 +440,132 @@ <h2 id="session-information">Session information<a class="anchor" aria-label="an
 </h2>
 <pre><code><span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
 <span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">setting </span> <span style="color: #555555; font-style: italic;">value</span></span></span>
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-<span><span class="co">#&gt;  readr          2.1.5   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readxl         1.4.3   <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rlang          1.1.3   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rmarkdown      2.26    <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rvest          1.0.4   <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sass           0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  scales         1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  selectr        0.4-2   <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sessioninfo    1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringi        1.8.3   <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringr        1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  systemfonts    1.0.6   <span style="color: #555555;">2024-03-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  textshaping    0.3.7   <span style="color: #555555;">2023-10-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tibble       * 3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyr        * 1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyselect     1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  timechange     0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tzdb           0.4.0   <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  utf8           1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vctrs          0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vroom          1.6.5   <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  withr          3.0.0   <span style="color: #555555;">2024-01-16</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xfun           0.43    <span style="color: #555555;">2024-03-25</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xml2           1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  yaml           2.3.8   <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
+<span><span class="co">#&gt;  backports      1.5.0   <span style="color: #555555;">2024-05-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocManager    1.30.25 <span style="color: #555555;">2024-08-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocParallel   1.38.0  <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  BiocStyle    * 2.32.1  <span style="color: #555555;">2024-06-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  bit            4.5.0   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bit64          4.5.2   <span style="color: #555555;">2024-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bookdown       0.41    <span style="color: #555555;">2024-10-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bslib          0.8.0   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cachem         1.1.0   <span style="color: #555555;">2024-05-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cellranger     1.1.0   <span style="color: #555555;">2016-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  checkmate      2.3.2   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cli            3.6.3   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  codetools      0.2-20  <span style="color: #555555;">2024-03-31</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  colorspace     2.1-1   <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  crayon         1.5.3   <span style="color: #555555;">2024-06-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  curl           5.2.3   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  decoupleR    * 2.9.7   <span style="color: #555555;">2024-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">Bioconductor</span></span></span>
+<span><span class="co">#&gt;  desc           1.4.3   <span style="color: #555555;">2023-12-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  digest         0.6.37  <span style="color: #555555;">2024-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dplyr        * 1.1.4   <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  evaluate       1.0.1   <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fansi          1.0.6   <span style="color: #555555;">2023-12-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  farver         2.1.2   <span style="color: #555555;">2024-05-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastmap        1.2.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fs             1.6.4   <span style="color: #555555;">2024-04-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  generics       0.1.3   <span style="color: #555555;">2022-07-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggplot2      * 3.5.1   <span style="color: #555555;">2024-04-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggrepel      * 0.9.6   <span style="color: #555555;">2024-09-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  glue           1.8.0   <span style="color: #555555;">2024-09-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gtable         0.3.5   <span style="color: #555555;">2024-04-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  highr          0.11    <span style="color: #555555;">2024-05-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  hms            1.1.3   <span style="color: #555555;">2023-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmltools      0.5.8.1 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmlwidgets    1.6.4   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httr           1.4.7   <span style="color: #555555;">2023-08-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  igraph         2.0.3   <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jquerylib      0.1.4   <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jsonlite       1.8.9   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  knitr          1.48    <span style="color: #555555;">2024-07-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  labeling       0.4.3   <span style="color: #555555;">2023-08-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  later          1.3.2   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lattice        0.22-6  <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  lifecycle      1.0.4   <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  logger         0.3.0   <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lubridate      1.9.3   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  magrittr       2.0.3   <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Matrix         1.7-1   <span style="color: #555555;">2024-10-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  munsell        0.5.1   <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  OmnipathR      3.12.4  <span style="color: #555555;">2024-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  parallelly     1.38.0  <span style="color: #555555;">2024-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pheatmap     * 1.0.12  <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pillar         1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgconfig      2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgdown        2.1.1   <span style="color: #555555;">2024-09-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  prettyunits    1.2.0   <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  progress       1.2.3   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  purrr          1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  R6             2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ragg           1.3.3   <span style="color: #555555;">2024-09-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rappdirs       0.3.3   <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RColorBrewer   1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rcpp           1.0.13  <span style="color: #555555;">2024-07-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readr          2.1.5   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readxl         1.4.3   <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rlang          1.1.4   <span style="color: #555555;">2024-06-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rmarkdown      2.28    <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rvest          1.0.4   <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sass           0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scales         1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  selectr        0.4-2   <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sessioninfo    1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringi        1.8.4   <span style="color: #555555;">2024-05-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringr        1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  systemfonts    1.1.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  textshaping    0.4.0   <span style="color: #555555;">2024-05-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tibble       * 3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyr        * 1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyselect     1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  timechange     0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tzdb           0.4.0   <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  utf8           1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vctrs          0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vroom          1.6.5   <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  withr          3.0.1   <span style="color: #555555;">2024-07-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xfun           0.48    <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xml2           1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  yaml           2.3.10  <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [1] /usr/local/lib/R/site-library</span></span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [2] /usr/local/lib/R/library</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span></code></pre>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
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 </div>
 
-  
 
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diff --git a/articles/tf_bk_files/figure-html/barplot-1.png b/articles/tf_bk_files/figure-html/barplot-1.png
index 2208d56a..8ba07c38 100644
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diff --git a/articles/tf_bk_files/figure-html/heatmap-1.png b/articles/tf_bk_files/figure-html/heatmap-1.png
index 86f5170b..f4d9ca37 100644
Binary files a/articles/tf_bk_files/figure-html/heatmap-1.png and b/articles/tf_bk_files/figure-html/heatmap-1.png differ
diff --git a/articles/tf_bk_files/figure-html/targets-1.png b/articles/tf_bk_files/figure-html/targets-1.png
index 8a09512d..93bb7e63 100644
Binary files a/articles/tf_bk_files/figure-html/targets-1.png and b/articles/tf_bk_files/figure-html/targets-1.png differ
diff --git a/articles/tf_sc.html b/articles/tf_sc.html
index 75bf2b40..2f416306 100644
--- a/articles/tf_sc.html
+++ b/articles/tf_sc.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="decoupleR">
 <title>Transcription factor activity inference from scRNA-seq • decoupleR</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -15,16 +14,11 @@
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 <script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <meta property="og:title" content="Transcription factor activity inference from scRNA-seq">
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-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -34,67 +28,42 @@
 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+<li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
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-    <span class="fas fa fas fa-university"></span>
-     
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-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -107,7 +76,7 @@
                         <h4 data-toc-skip class="author">Pau
 Badia-i-Mompel</h4>
             <address class="author_afil">
-      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/vignettes/tf_sc.Rmd" class="external-link"><code>vignettes/tf_sc.Rmd</code></a></small>
+      Heidelberg Universiy<br><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/vignettes/tf_sc.Rmd" class="external-link"><code>vignettes/tf_sc.Rmd</code></a></small>
       <div class="d-none name"><code>tf_sc.Rmd</code></div>
     </address>
 </div>
@@ -152,7 +121,13 @@ <h2 id="loading-the-data-set">Loading the data-set<a class="anchor" aria-label="
 <span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/file.path.html" class="external-link">file.path</a></span><span class="op">(</span><span class="va">inputs_dir</span>, <span class="st">"sc_data.rds"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <p>We can observe that we have different cell types:</p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, reduction <span class="op">=</span> <span class="st">"umap"</span>, label <span class="op">=</span> <span class="cn">TRUE</span>, pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="va">p</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, </span>
+<span>                     reduction <span class="op">=</span> <span class="st">"umap"</span>, </span>
+<span>                     label <span class="op">=</span> <span class="cn">TRUE</span>, </span>
+<span>                     pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>     <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p</span></span></code></pre></div>
 <p><img src="tf_sc_files/figure-html/umap-1.png" width="700"></p>
 </div>
 <div class="section level2">
@@ -173,7 +148,9 @@ <h2 id="collectri-network">CollecTRI network<a class="anchor" aria-label="anchor
 complexes or splits them into subunits, by default we recommend to keep
 complexes together.</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/get_collectri.html">get_collectri</a></span><span class="op">(</span>organism<span class="op">=</span><span class="st">'human'</span>, split_complexes<span class="op">=</span><span class="cn">FALSE</span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="va">net</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/get_collectri.html">get_collectri</a></span><span class="op">(</span>organism <span class="op">=</span> <span class="st">'human'</span>, </span>
+<span>                                split_complexes <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">net</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 43,178 × 3</span></span></span>
 <span><span class="co">#&gt;    source target   mor</span></span>
@@ -213,8 +190,13 @@ <h2 id="activity-inference-with-univariate-linear-model-ulm">Activity inference
 <span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">RNA</span><span class="op">@</span><span class="va">data</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Run ulm</span></span>
-<span><span class="va">acts</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat<span class="op">=</span><span class="va">mat</span>, net<span class="op">=</span><span class="va">net</span>, .source<span class="op">=</span><span class="st">'source'</span>, .target<span class="op">=</span><span class="st">'target'</span>,</span>
-<span>                .mor<span class="op">=</span><span class="st">'mor'</span>, minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span><span class="va">acts</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu"><a href="../reference/run_ulm.html">run_ulm</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">mat</span>, </span>
+<span>                           net <span class="op">=</span> <span class="va">net</span>, </span>
+<span>                           .source <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                           .target <span class="op">=</span> <span class="st">'target'</span>,</span>
+<span>                           .mor<span class="op">=</span><span class="st">'mor'</span>, </span>
+<span>                           minsize <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span>
+<span></span>
 <span><span class="va">acts</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 80,640 × 5</span></span></span>
 <span><span class="co">#&gt;    statistic source condition         score p_value</span></span>
@@ -239,16 +221,17 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># Extract ulm and store it in tfsulm in pbmc</span></span>
 <span><span class="va">data</span><span class="op">[[</span><span class="st">'tfsulm'</span><span class="op">]</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="va">acts</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'source'</span>, names_from <span class="op">=</span> <span class="st">'condition'</span>,</span>
-<span>              values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'source'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/CreateAssayObject.html" class="external-link">CreateAssayObject</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span></span>
+<span>                    <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'source'</span>, </span>
+<span>                                       names_from <span class="op">=</span> <span class="st">'condition'</span>,</span>
+<span>                                       values_from <span class="op">=</span> <span class="st">'score'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                    <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'source'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                    <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/CreateAssayObject.html" class="external-link">CreateAssayObject</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Change assay</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"tfsulm"</span></span>
+<span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"tfsulm"</span></span>
 <span></span>
 <span><span class="co"># Scale the data</span></span>
-<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/ScaleData.html" class="external-link">ScaleData</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
+<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/ScaleData.html" class="external-link">ScaleData</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
 <span><span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">tfsulm</span><span class="op">@</span><span class="va">data</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">tfsulm</span><span class="op">@</span><span class="va">scale.data</span></span></code></pre></div>
 <p>This new assay can be used to plot activities. Here we observe the
 activity inferred for PAX5 across cells, which it is particulary active
@@ -258,15 +241,30 @@ <h2 id="visualization">Visualization<a class="anchor" aria-label="anchor" href="
 readouts of a given TF, as an example here is the gene expression of
 PAX5, which is not very informative by itself:</p>
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">p1</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, reduction <span class="op">=</span> <span class="st">"umap"</span>, label <span class="op">=</span> <span class="cn">TRUE</span>, pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'Cell types'</span><span class="op">)</span></span>
-<span><span class="va">p2</span> <span class="op">&lt;-</span> <span class="op">(</span><span class="fu"><a href="https://satijalab.org/seurat/reference/FeaturePlot.html" class="external-link">FeaturePlot</a></span><span class="op">(</span><span class="va">data</span>, features <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"PAX5"</span><span class="op">)</span><span class="op">)</span> <span class="op">&amp;</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_gradient.html" class="external-link">scale_colour_gradient2</a></span><span class="op">(</span>low <span class="op">=</span> <span class="st">'blue'</span>, mid <span class="op">=</span> <span class="st">'white'</span>, high <span class="op">=</span> <span class="st">'red'</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'PAX5 activity'</span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"RNA"</span></span>
-<span><span class="va">p3</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://satijalab.org/seurat/reference/FeaturePlot.html" class="external-link">FeaturePlot</a></span><span class="op">(</span><span class="va">data</span>, features <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"PAX5"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'PAX5 expression'</span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"tfsulm"</span></span>
-<span><span class="va">p1</span> <span class="op">|</span> <span class="va">p2</span> <span class="op">|</span> <span class="va">p3</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="va">p1</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/DimPlot.html" class="external-link">DimPlot</a></span><span class="op">(</span><span class="va">data</span>, </span>
+<span>                      reduction <span class="op">=</span> <span class="st">"umap"</span>, </span>
+<span>                      label <span class="op">=</span> <span class="cn">TRUE</span>, </span>
+<span>                      pt.size <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/SeuratTheme.html" class="external-link">NoLegend</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'Cell types'</span><span class="op">)</span></span>
+<span></span>
+<span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">2</span>, <span class="fl">10</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">p2</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/FeaturePlot.html" class="external-link">FeaturePlot</a></span><span class="op">(</span><span class="va">data</span>, features <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"PAX5"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_gradient.html" class="external-link">scale_colour_gradient2</a></span><span class="op">(</span>low <span class="op">=</span> <span class="va">colors</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span>, mid <span class="op">=</span> <span class="st">'white'</span>, high <span class="op">=</span> <span class="va">colors</span><span class="op">[</span><span class="fl">2</span><span class="op">]</span><span class="op">)</span> <span class="op">+</span></span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'PAX5 activity'</span><span class="op">)</span></span>
+<span></span>
+<span></span>
+<span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span>object <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"RNA"</span></span>
+<span><span class="va">p3</span> <span class="op">&lt;-</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://satijalab.org/seurat/reference/FeaturePlot.html" class="external-link">FeaturePlot</a></span><span class="op">(</span><span class="va">data</span>, </span>
+<span>                          features <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"PAX5"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>      <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggtitle</a></span><span class="op">(</span><span class="st">'PAX5 expression'</span><span class="op">)</span></span>
+<span></span>
+<span><span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/DefaultAssay.html" class="external-link">DefaultAssay</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="st">"tfsulm"</span></span>
+<span></span>
+<span><span class="va">p</span> <span class="op">&lt;-</span> <span class="va">p1</span> <span class="op">|</span> <span class="va">p2</span> <span class="op">|</span> <span class="va">p3</span></span>
+<span><span class="va">p</span></span></code></pre></div>
 <p><img src="tf_sc_files/figure-html/projected_acts-1.png" width="1152"></p>
 </div>
 <div class="section level2">
@@ -276,39 +274,50 @@ <h2 id="exploration">Exploration<a class="anchor" aria-label="anchor" href="#exp
 more variable TFs:</p>
 <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">n_tfs</span> <span class="op">&lt;-</span> <span class="fl">25</span></span>
+<span></span>
 <span><span class="co"># Extract activities from object as a long dataframe</span></span>
 <span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/t.html" class="external-link">t</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="va">data</span><span class="op">@</span><span class="va">assays</span><span class="op">$</span><span class="va">tfsulm</span><span class="op">@</span><span class="va">data</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>cluster <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/pkg/SeuratObject/man/Idents.html" class="external-link">Idents</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">pivot_longer</a></span><span class="op">(</span>cols <span class="op">=</span> <span class="op">-</span><span class="va">cluster</span>, names_to <span class="op">=</span> <span class="st">"source"</span>, values_to <span class="op">=</span> <span class="st">"score"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">cluster</span>, <span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>mean <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span></span>
+<span>      <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>cluster <span class="op">=</span> <span class="fu">Seurat</span><span class="fu">::</span><span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/Idents.html" class="external-link">Idents</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">pivot_longer</a></span><span class="op">(</span>cols <span class="op">=</span> <span class="op">-</span><span class="va">cluster</span>, </span>
+<span>                          names_to <span class="op">=</span> <span class="st">"source"</span>, </span>
+<span>                          values_to <span class="op">=</span> <span class="st">"score"</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">cluster</span>, <span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>      <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>mean <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Get top tfs with more variable means across clusters</span></span>
 <span><span class="va">tfs</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>std <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="va">mean</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="op">-</span><span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs</a></span><span class="op">(</span><span class="va">std</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">n_tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>std <span class="op">=</span> <span class="fu">stats</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="va">mean</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="op">-</span><span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">abs</a></span><span class="op">(</span><span class="va">std</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">n_tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>       <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">source</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Subset long data frame to top tfs and transform to wide matrix</span></span>
 <span><span class="va">top_acts_mat</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">source</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'cluster'</span>, names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
-<span>              values_from <span class="op">=</span> <span class="st">'mean'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'cluster'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>                <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">source</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">tfs</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html" class="external-link">pivot_wider</a></span><span class="op">(</span>id_cols <span class="op">=</span> <span class="st">'cluster'</span>, </span>
+<span>                                   names_from <span class="op">=</span> <span class="st">'source'</span>,</span>
+<span>                                   values_from <span class="op">=</span> <span class="st">'mean'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/rownames.html" class="external-link">column_to_rownames</a></span><span class="op">(</span><span class="st">'cluster'</span><span class="op">)</span> <span class="op"><a href="../reference/pipe.html">%&gt;%</a></span></span>
+<span>                <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">as.matrix</a></span><span class="op">(</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Choose color palette</span></span>
-<span><span class="va">palette_length</span> <span class="op">=</span> <span class="fl">100</span></span>
-<span><span class="va">my_color</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Darkblue"</span>, <span class="st">"white"</span>,<span class="st">"red"</span><span class="op">)</span><span class="op">)</span><span class="op">(</span><span class="va">palette_length</span><span class="op">)</span></span>
+<span><span class="va">colors</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rev.html" class="external-link">rev</a></span><span class="op">(</span><span class="fu">RColorBrewer</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html" class="external-link">brewer.pal</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">11</span>, name <span class="op">=</span> <span class="st">"RdBu"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">colors.use</span> <span class="op">&lt;-</span> <span class="fu">grDevices</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/grDevices/colorRamp.html" class="external-link">colorRampPalette</a></span><span class="op">(</span>colors <span class="op">=</span> <span class="va">colors</span><span class="op">)</span><span class="op">(</span><span class="fl">100</span><span class="op">)</span></span>
 <span></span>
-<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">3</span>, <span class="fl">0</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
-<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">3</span>, length.out<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="va">palette_length</span><span class="op">/</span><span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">my_breaks</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="op">-</span><span class="fl">2</span>, <span class="fl">0</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span>,</span>
+<span>               <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">2</span>, length.out <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">floor</a></span><span class="op">(</span><span class="fl">100</span> <span class="op">/</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Plot</span></span>
-<span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span><span class="va">top_acts_mat</span>, border_color <span class="op">=</span> <span class="cn">NA</span>, color<span class="op">=</span><span class="va">my_color</span>, breaks <span class="op">=</span> <span class="va">my_breaks</span><span class="op">)</span> </span></code></pre></div>
+<span><span class="fu">pheatmap</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/pheatmap/man/pheatmap.html" class="external-link">pheatmap</a></span><span class="op">(</span>mat <span class="op">=</span> <span class="va">top_acts_mat</span>,</span>
+<span>                   color <span class="op">=</span> <span class="va">colors.use</span>,</span>
+<span>                   border_color <span class="op">=</span> <span class="st">"white"</span>,</span>
+<span>                   breaks <span class="op">=</span> <span class="va">my_breaks</span>,</span>
+<span>                   cellwidth <span class="op">=</span> <span class="fl">15</span>,</span>
+<span>                   cellheight <span class="op">=</span> <span class="fl">15</span>,</span>
+<span>                   treeheight_row <span class="op">=</span> <span class="fl">20</span>,</span>
+<span>                   treeheight_col <span class="op">=</span> <span class="fl">20</span><span class="op">)</span> </span></code></pre></div>
 <p><img src="tf_sc_files/figure-html/mean_acts-1.png" width="700"></p>
 <p>Here we can observe other known marker TFs appearing, EBF1 for B
 cells RFX5 for the myeloid lineage and EOMES for the lymphoid.</p>
@@ -318,197 +327,195 @@ <h2 id="session-information">Session information<a class="anchor" aria-label="an
 </h2>
 <pre><code><span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
 <span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">setting </span> <span style="color: #555555; font-style: italic;">value</span></span></span>
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-<span><span class="co">#&gt;  os       Ubuntu 22.04.4 LTS</span></span>
+<span><span class="co">#&gt;  version  R version 4.4.1 (2024-06-14)</span></span>
+<span><span class="co">#&gt;  os       Ubuntu 22.04.5 LTS</span></span>
 <span><span class="co">#&gt;  system   x86_64, linux-gnu</span></span>
 <span><span class="co">#&gt;  ui       X11</span></span>
 <span><span class="co">#&gt;  language en</span></span>
 <span><span class="co">#&gt;  collate  en_US.UTF-8</span></span>
 <span><span class="co">#&gt;  ctype    en_US.UTF-8</span></span>
 <span><span class="co">#&gt;  tz       UTC</span></span>
-<span><span class="co">#&gt;  date     2024-04-11</span></span>
-<span><span class="co">#&gt;  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown)</span></span>
+<span><span class="co">#&gt;  date     2024-10-19</span></span>
+<span><span class="co">#&gt;  pandoc   3.4 @ /usr/bin/ (via rmarkdown)</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span>
-<span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">package         </span> <span style="color: #555555; font-style: italic;">*</span> <span style="color: #555555; font-style: italic;">version </span> <span style="color: #555555; font-style: italic;">date (UTC)</span> <span style="color: #555555; font-style: italic;">lib</span> <span style="color: #555555; font-style: italic;">source</span></span></span>
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-<span><span class="co">#&gt;  BiocParallel       1.37.1   <span style="color: #555555;">2024-03-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
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-<span><span class="co">#&gt;  bit                4.0.5    <span style="color: #555555;">2022-11-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  bit64              4.0.5    <span style="color: #555555;">2020-08-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  bookdown           0.38     <span style="color: #555555;">2024-03-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  bslib              0.7.0    <span style="color: #555555;">2024-03-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  cachem             1.0.8    <span style="color: #555555;">2023-05-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  cellranger         1.1.0    <span style="color: #555555;">2016-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  checkmate          2.3.1    <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  cli                3.6.2    <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  cluster            2.1.6    <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  codetools          0.2-20   <span style="color: #555555;">2024-03-31</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  colorspace         2.1-0    <span style="color: #555555;">2023-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  cowplot            1.1.3    <span style="color: #555555;">2024-01-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  crayon             1.5.2    <span style="color: #555555;">2022-09-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  curl               5.2.1    <span style="color: #555555;">2024-03-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  data.table         1.15.4   <span style="color: #555555;">2024-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  decoupleR        * 2.9.7    <span style="color: #555555;">2024-04-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">Bioconductor</span></span></span>
-<span><span class="co">#&gt;  deldir             2.0-4    <span style="color: #555555;">2024-02-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  desc               1.4.3    <span style="color: #555555;">2023-12-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  digest             0.6.35   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  dotCall64          1.1-1    <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  evaluate           0.23     <span style="color: #555555;">2023-11-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
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-<span><span class="co">#&gt;  fastDummies        1.7.3    <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  fastmap            1.1.1    <span style="color: #555555;">2023-02-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  fitdistrplus       1.1-11   <span style="color: #555555;">2023-04-25</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  fs                 1.6.3    <span style="color: #555555;">2023-07-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  future             1.33.2   <span style="color: #555555;">2024-03-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  future.apply       1.11.2   <span style="color: #555555;">2024-03-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  generics           0.1.3    <span style="color: #555555;">2022-07-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ggplot2          * 3.5.0    <span style="color: #555555;">2024-02-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ggrepel            0.9.5    <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ggridges           0.5.6    <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  globals            0.16.3   <span style="color: #555555;">2024-03-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  glue               1.7.0    <span style="color: #555555;">2024-01-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  goftest            1.2-3    <span style="color: #555555;">2021-10-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  gridExtra          2.3      <span style="color: #555555;">2017-09-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  gtable             0.3.4    <span style="color: #555555;">2023-08-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  highr              0.10     <span style="color: #555555;">2022-12-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  hms                1.1.3    <span style="color: #555555;">2023-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  htmltools          0.5.8.1  <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  htmlwidgets        1.6.4    <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  httpuv             1.6.15   <span style="color: #555555;">2024-03-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  httr               1.4.7    <span style="color: #555555;">2023-08-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ica                1.0-3    <span style="color: #555555;">2022-07-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  igraph             2.0.3    <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  irlba              2.3.5.1  <span style="color: #555555;">2022-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  jquerylib          0.1.4    <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  jsonlite           1.8.8    <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  KernSmooth         2.23-22  <span style="color: #555555;">2023-07-10</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  knitr              1.46     <span style="color: #555555;">2024-04-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  labeling           0.4.3    <span style="color: #555555;">2023-08-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  later              1.3.2    <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lattice            0.22-6   <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lazyeval           0.2.2    <span style="color: #555555;">2019-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  leiden             0.4.3.1  <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lifecycle          1.0.4    <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  listenv            0.9.1    <span style="color: #555555;">2024-01-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lmtest             0.9-40   <span style="color: #555555;">2022-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  logger             0.3.0    <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  lubridate          1.9.3    <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  magrittr           2.0.3    <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  MASS               7.3-60.2 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[2]</span> <span style="color: #BB00BB; font-weight: bold;">local</span></span></span>
-<span><span class="co">#&gt;  Matrix             1.7-0    <span style="color: #555555;">2024-03-22</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  matrixStats        1.3.0    <span style="color: #555555;">2024-04-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  memoise            2.0.1    <span style="color: #555555;">2021-11-26</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  mime               0.12     <span style="color: #555555;">2021-09-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  miniUI             0.1.1.1  <span style="color: #555555;">2018-05-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  munsell            0.5.1    <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  nlme               3.1-164  <span style="color: #555555;">2023-11-27</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  OmnipathR          3.11.10  <span style="color: #555555;">2024-03-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
-<span><span class="co">#&gt;  parallelly         1.37.1   <span style="color: #555555;">2024-02-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  patchwork        * 1.2.0    <span style="color: #555555;">2024-01-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pbapply            1.7-2    <span style="color: #555555;">2023-06-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pheatmap         * 1.0.12   <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pillar             1.9.0    <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgconfig          2.0.3    <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  pkgdown            2.0.8    <span style="color: #555555;">2024-04-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  plotly             4.10.4   <span style="color: #555555;">2024-01-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  plyr               1.8.9    <span style="color: #555555;">2023-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  png                0.1-8    <span style="color: #555555;">2022-11-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  polyclip           1.10-6   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  prettyunits        1.2.0    <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  progress           1.2.3    <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  progressr          0.14.0   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  promises           1.3.0    <span style="color: #555555;">2024-04-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  purrr              1.0.2    <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  R6                 2.5.1    <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ragg               1.3.0    <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RANN               2.6.1    <span style="color: #555555;">2019-01-08</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rappdirs           0.3.3    <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RColorBrewer       1.1-3    <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Rcpp               1.0.12   <span style="color: #555555;">2024-01-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RcppAnnoy          0.0.22   <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RcppHNSW           0.6.0    <span style="color: #555555;">2024-02-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readr              2.1.5    <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  readxl             1.4.3    <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  reshape2           1.4.4    <span style="color: #555555;">2020-04-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  reticulate         1.35.0   <span style="color: #555555;">2024-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rlang              1.1.3    <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rmarkdown          2.26     <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  ROCR               1.0-11   <span style="color: #555555;">2020-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  RSpectra           0.16-1   <span style="color: #555555;">2022-04-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Rtsne              0.17     <span style="color: #555555;">2023-12-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  rvest              1.0.4    <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sass               0.4.9    <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  scales             1.3.0    <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  scattermore        1.2      <span style="color: #555555;">2023-06-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sctransform        0.4.1    <span style="color: #555555;">2023-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  selectr            0.4-2    <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sessioninfo        1.2.2    <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  Seurat           * 5.0.3    <span style="color: #555555;">2024-03-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  SeuratObject     * 5.0.1    <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  shiny              1.8.1.1  <span style="color: #555555;">2024-04-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  sp               * 2.1-3    <span style="color: #555555;">2024-01-30</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spam               2.10-0   <span style="color: #555555;">2023-10-23</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.data      3.0-4    <span style="color: #555555;">2024-01-15</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.explore   3.2-7    <span style="color: #555555;">2024-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.geom      3.2-9    <span style="color: #555555;">2024-02-28</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.random    3.2-3    <span style="color: #555555;">2024-02-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.sparse    3.0-3    <span style="color: #555555;">2023-10-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  spatstat.utils     3.0-4    <span style="color: #555555;">2023-10-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringi            1.8.3    <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  stringr            1.5.1    <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  survival           3.5-8    <span style="color: #555555;">2024-02-14</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  systemfonts        1.0.6    <span style="color: #555555;">2024-03-07</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tensor             1.5      <span style="color: #555555;">2012-05-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  textshaping        0.3.7    <span style="color: #555555;">2023-10-09</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tibble           * 3.2.1    <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyr            * 1.3.1    <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tidyselect         1.2.1    <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  timechange         0.3.0    <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  tzdb               0.4.0    <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  utf8               1.2.4    <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  uwot               0.1.16   <span style="color: #555555;">2023-06-29</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vctrs              0.6.5    <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  viridisLite        0.4.2    <span style="color: #555555;">2023-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  vroom              1.6.5    <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  withr              3.0.0    <span style="color: #555555;">2024-01-16</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xfun               0.43     <span style="color: #555555;">2024-03-25</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xml2               1.3.6    <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  xtable             1.8-4    <span style="color: #555555;">2019-04-21</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  yaml               2.3.8    <span style="color: #555555;">2023-12-11</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
-<span><span class="co">#&gt;  zoo                1.8-12   <span style="color: #555555;">2023-04-13</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">CRAN (R 4.5.0)</span></span></span>
+<span><span class="co">#&gt;  <span style="color: #555555; font-style: italic;">package         </span> <span style="color: #555555; font-style: italic;">*</span> <span style="color: #555555; font-style: italic;">version</span> <span style="color: #555555; font-style: italic;">date (UTC)</span> <span style="color: #555555; font-style: italic;">lib</span> <span style="color: #555555; font-style: italic;">source</span></span></span>
+<span><span class="co">#&gt;  abind              1.4-8   <span style="color: #555555;">2024-09-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  backports          1.5.0   <span style="color: #555555;">2024-05-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocManager        1.30.25 <span style="color: #555555;">2024-08-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  BiocParallel       1.38.0  <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  BiocStyle        * 2.32.1  <span style="color: #555555;">2024-06-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  bit                4.5.0   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bit64              4.5.2   <span style="color: #555555;">2024-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bookdown           0.41    <span style="color: #555555;">2024-10-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  bslib              0.8.0   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cachem             1.1.0   <span style="color: #555555;">2024-05-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cellranger         1.1.0   <span style="color: #555555;">2016-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  checkmate          2.3.2   <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cli                3.6.3   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cluster            2.1.6   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  codetools          0.2-20  <span style="color: #555555;">2024-03-31</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  colorspace         2.1-1   <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  cowplot            1.1.3   <span style="color: #555555;">2024-01-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  crayon             1.5.3   <span style="color: #555555;">2024-06-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  curl               5.2.3   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  data.table         1.16.2  <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  decoupleR        * 2.9.7   <span style="color: #555555;">2024-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #555555;">Bioconductor</span></span></span>
+<span><span class="co">#&gt;  deldir             2.0-4   <span style="color: #555555;">2024-02-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  desc               1.4.3   <span style="color: #555555;">2023-12-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  digest             0.6.37  <span style="color: #555555;">2024-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dotCall64          1.2     <span style="color: #555555;">2024-10-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  dplyr            * 1.1.4   <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  evaluate           1.0.1   <span style="color: #555555;">2024-10-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fansi              1.0.6   <span style="color: #555555;">2023-12-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  farver             2.1.2   <span style="color: #555555;">2024-05-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastDummies        1.7.4   <span style="color: #555555;">2024-08-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fastmap            1.2.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fitdistrplus       1.2-1   <span style="color: #555555;">2024-07-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  fs                 1.6.4   <span style="color: #555555;">2024-04-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  future             1.34.0  <span style="color: #555555;">2024-07-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  future.apply       1.11.2  <span style="color: #555555;">2024-03-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  generics           0.1.3   <span style="color: #555555;">2022-07-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggplot2          * 3.5.1   <span style="color: #555555;">2024-04-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggrepel            0.9.6   <span style="color: #555555;">2024-09-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ggridges           0.5.6   <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  globals            0.16.3  <span style="color: #555555;">2024-03-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  glue               1.8.0   <span style="color: #555555;">2024-09-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  goftest            1.2-3   <span style="color: #555555;">2021-10-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gridExtra          2.3     <span style="color: #555555;">2017-09-09</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  gtable             0.3.5   <span style="color: #555555;">2024-04-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  highr              0.11    <span style="color: #555555;">2024-05-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  hms                1.1.3   <span style="color: #555555;">2023-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmltools          0.5.8.1 <span style="color: #555555;">2024-04-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  htmlwidgets        1.6.4   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httpuv             1.6.15  <span style="color: #555555;">2024-03-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  httr               1.4.7   <span style="color: #555555;">2023-08-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ica                1.0-3   <span style="color: #555555;">2022-07-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  igraph             2.0.3   <span style="color: #555555;">2024-03-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  irlba              2.3.5.1 <span style="color: #555555;">2022-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jquerylib          0.1.4   <span style="color: #555555;">2021-04-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  jsonlite           1.8.9   <span style="color: #555555;">2024-09-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  KernSmooth         2.23-24 <span style="color: #555555;">2024-05-17</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  knitr              1.48    <span style="color: #555555;">2024-07-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  labeling           0.4.3   <span style="color: #555555;">2023-08-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  later              1.3.2   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lattice            0.22-6  <span style="color: #555555;">2024-03-20</span> <span style="color: #555555;">[2]</span> <span style="color: #555555;">CRAN (R 4.4.1)</span></span></span>
+<span><span class="co">#&gt;  lazyeval           0.2.2   <span style="color: #555555;">2019-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  leiden             0.4.3.1 <span style="color: #555555;">2023-11-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lifecycle          1.0.4   <span style="color: #555555;">2023-11-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  listenv            0.9.1   <span style="color: #555555;">2024-01-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lmtest             0.9-40  <span style="color: #555555;">2022-03-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  logger             0.3.0   <span style="color: #555555;">2024-03-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  lubridate          1.9.3   <span style="color: #555555;">2023-09-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  magrittr           2.0.3   <span style="color: #555555;">2022-03-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  MASS               7.3-61  <span style="color: #555555;">2024-06-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  Matrix             1.7-1   <span style="color: #555555;">2024-10-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  matrixStats        1.4.1   <span style="color: #555555;">2024-09-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  mime               0.12    <span style="color: #555555;">2021-09-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  miniUI             0.1.1.1 <span style="color: #555555;">2018-05-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  munsell            0.5.1   <span style="color: #555555;">2024-04-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  nlme               3.1-166 <span style="color: #555555;">2024-08-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  OmnipathR          3.12.4  <span style="color: #555555;">2024-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">Bioconduc~</span></span></span>
+<span><span class="co">#&gt;  parallelly         1.38.0  <span style="color: #555555;">2024-07-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  patchwork        * 1.3.0   <span style="color: #555555;">2024-09-16</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pbapply            1.7-2   <span style="color: #555555;">2023-06-27</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pheatmap         * 1.0.12  <span style="color: #555555;">2019-01-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pillar             1.9.0   <span style="color: #555555;">2023-03-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgconfig          2.0.3   <span style="color: #555555;">2019-09-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  pkgdown            2.1.1   <span style="color: #555555;">2024-09-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  plotly             4.10.4  <span style="color: #555555;">2024-01-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  plyr               1.8.9   <span style="color: #555555;">2023-10-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  png                0.1-8   <span style="color: #555555;">2022-11-29</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  polyclip           1.10-7  <span style="color: #555555;">2024-07-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  prettyunits        1.2.0   <span style="color: #555555;">2023-09-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  progress           1.2.3   <span style="color: #555555;">2023-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  progressr          0.14.0  <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  promises           1.3.0   <span style="color: #555555;">2024-04-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  purrr              1.0.2   <span style="color: #555555;">2023-08-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  R6                 2.5.1   <span style="color: #555555;">2021-08-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ragg               1.3.3   <span style="color: #555555;">2024-09-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RANN               2.6.2   <span style="color: #555555;">2024-08-25</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rappdirs           0.3.3   <span style="color: #555555;">2021-01-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RColorBrewer       1.1-3   <span style="color: #555555;">2022-04-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rcpp               1.0.13  <span style="color: #555555;">2024-07-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RcppAnnoy          0.0.22  <span style="color: #555555;">2024-01-23</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RcppHNSW           0.6.0   <span style="color: #555555;">2024-02-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readr              2.1.5   <span style="color: #555555;">2024-01-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  readxl             1.4.3   <span style="color: #555555;">2023-07-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  reshape2           1.4.4   <span style="color: #555555;">2020-04-09</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  reticulate         1.39.0  <span style="color: #555555;">2024-09-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rlang              1.1.4   <span style="color: #555555;">2024-06-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rmarkdown          2.28    <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  ROCR               1.0-11  <span style="color: #555555;">2020-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  RSpectra           0.16-2  <span style="color: #555555;">2024-07-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Rtsne              0.17    <span style="color: #555555;">2023-12-07</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  rvest              1.0.4   <span style="color: #555555;">2024-02-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sass               0.4.9   <span style="color: #555555;">2024-03-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scales             1.3.0   <span style="color: #555555;">2023-11-28</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  scattermore        1.2     <span style="color: #555555;">2023-06-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sctransform        0.4.1   <span style="color: #555555;">2023-10-19</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  selectr            0.4-2   <span style="color: #555555;">2019-11-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sessioninfo        1.2.2   <span style="color: #555555;">2021-12-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  Seurat           * 5.1.0   <span style="color: #555555;">2024-05-10</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  SeuratObject     * 5.0.2   <span style="color: #555555;">2024-05-08</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  shiny              1.9.1   <span style="color: #555555;">2024-08-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  sp               * 2.1-4   <span style="color: #555555;">2024-04-30</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spam               2.11-0  <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.data      3.1-2   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.explore   3.3-2   <span style="color: #555555;">2024-08-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.geom      3.3-3   <span style="color: #555555;">2024-09-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.random    3.3-2   <span style="color: #555555;">2024-09-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.sparse    3.1-0   <span style="color: #555555;">2024-06-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.univar    3.0-1   <span style="color: #555555;">2024-09-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  spatstat.utils     3.1-0   <span style="color: #555555;">2024-08-17</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringi            1.8.4   <span style="color: #555555;">2024-05-06</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  stringr            1.5.1   <span style="color: #555555;">2023-11-14</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  survival           3.7-0   <span style="color: #555555;">2024-06-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM (R 4.4.0)</span></span></span>
+<span><span class="co">#&gt;  systemfonts        1.1.0   <span style="color: #555555;">2024-05-15</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tensor             1.5     <span style="color: #555555;">2012-05-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  textshaping        0.4.0   <span style="color: #555555;">2024-05-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tibble           * 3.2.1   <span style="color: #555555;">2023-03-20</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyr            * 1.3.1   <span style="color: #555555;">2024-01-24</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tidyselect         1.2.1   <span style="color: #555555;">2024-03-11</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  timechange         0.3.0   <span style="color: #555555;">2024-01-18</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  tzdb               0.4.0   <span style="color: #555555;">2023-05-12</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  utf8               1.2.4   <span style="color: #555555;">2023-10-22</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  uwot               0.2.2   <span style="color: #555555;">2024-04-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vctrs              0.6.5   <span style="color: #555555;">2023-12-01</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  viridisLite        0.4.2   <span style="color: #555555;">2023-05-02</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  vroom              1.6.5   <span style="color: #555555;">2023-12-05</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  withr              3.0.1   <span style="color: #555555;">2024-07-31</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xfun               0.48    <span style="color: #555555;">2024-10-03</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xml2               1.3.6   <span style="color: #555555;">2023-12-04</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  xtable             1.8-4   <span style="color: #555555;">2019-04-21</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  yaml               2.3.10  <span style="color: #555555;">2024-07-26</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
+<span><span class="co">#&gt;  zoo                1.8-12  <span style="color: #555555;">2023-04-13</span> <span style="color: #555555;">[1]</span> <span style="color: #BB00BB; font-weight: bold;">RSPM</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [1] /usr/local/lib/R/site-library</span></span></span>
 <span><span class="co">#&gt; <span style="color: #555555;"> [2] /usr/local/lib/R/library</span></span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; <span style="color: #00BBBB; font-weight: bold;">──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────</span></span></span></code></pre>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/articles/tf_sc_files/figure-html/mean_acts-1.png b/articles/tf_sc_files/figure-html/mean_acts-1.png
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diff --git a/articles/tf_sc_files/figure-html/projected_acts-1.png b/articles/tf_sc_files/figure-html/projected_acts-1.png
index 372b3ad1..47e1f468 100644
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diff --git a/authors.html b/authors.html
index 7c98c2e8..d81a462b 100644
--- a/authors.html
+++ b/authors.html
@@ -1,8 +1,5 @@
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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@@ -10,62 +7,36 @@
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     <a class="navbar-brand me-2" href="index.html">decoupleR</a>
 
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+    <li><a class="dropdown-item" href="articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="news/index.html">Changelog</a></li>
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@@ -73,9 +44,9 @@
       <img src="logo.svg" class="logo" alt=""><h1>Authors and Citation</h1>
     </div>
 
-    <div class="section level2 citation">
+    <div class="section level2">
       <h2>Authors</h2>
-      
+
       <ul class="list-unstyled"><li>
           <p><strong>Pau Badia-i-Mompel</strong>. Author, maintainer. <a href="https://orcid.org/0000-0002-1004-3923" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
@@ -122,13 +93,13 @@ <h2>Authors</h2>
         </li>
       </ul></div>
 
-    <div class="section level2 citation">
+    <div class="section level2">
       <h2 id="citation">Citation</h2>
-      <p><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/inst/CITATION" class="external-link"><code>inst/CITATION</code></a></small></p>
+      <p><small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/inst/CITATION" class="external-link"><code>inst/CITATION</code></a></small></p>
 
-      <p>Badia-i-Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov 
-  D., Müller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O. 
-  and Saez-Rodriguez J. 2022. decoupleR: Ensemble of computational methods to 
+      <p>Badia-i-Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov
+  D., Müller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O.
+  and Saez-Rodriguez J. 2022. decoupleR: Ensemble of computational methods to
   infer biological activities from omics data. Bioinformatics Advances.
   https://doi.org/10.1093/bioadv/vbac016</p>
       <pre>@Article{,
@@ -139,23 +110,24 @@ <h2 id="citation">Citation</h2>
   doi = {https://doi.org/10.1093/bioadv/vbac016},
 }</pre>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
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.nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-sm .navbar-nav-scroll{overflow:visible}.navbar-expand-sm .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-sm .navbar-toggler{display:none}.navbar-expand-sm .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-sm .offcanvas .offcanvas-header{display:none}.navbar-expand-sm .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 768px){.navbar-expand-md{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-md .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-md .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-md .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-md .navbar-nav-scroll{overflow:visible}.navbar-expand-md .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-md .navbar-toggler{display:none}.navbar-expand-md .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-md .offcanvas .offcanvas-header{display:none}.navbar-expand-md .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 1200px){.navbar-expand-xl{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-xl .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-xl .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-xl .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-xl .navbar-nav-scroll{overflow:visible}.navbar-expand-xl .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-xl .navbar-toggler{display:none}.navbar-expand-xl .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xl .offcanvas .offcanvas-header{display:none}.navbar-expand-xl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 1400px){.navbar-expand-xxl{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-xxl .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-xxl .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-xxl .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-xxl .navbar-nav-scroll{overflow:visible}.navbar-expand-xxl .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-xxl .navbar-toggler{display:none}.navbar-expand-xxl .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme="dark"]{--bs-navbar-color: rgba(0,0,0,0.55);--bs-navbar-hover-color: #fff;--bs-navbar-disabled-color: rgba(0,0,0,0.25);--bs-navbar-active-color: #000;--bs-navbar-brand-color: #000;--bs-navbar-brand-hover-color: #000;--bs-navbar-toggler-border-color: rgba(0,0,0,0.1);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%280,0,0,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme="dark"] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%280,0,0,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: .5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: var(--bs-border-width);--bs-card-border-color: var(--bs-border-color-translucent);--bs-card-border-radius: var(--bs-border-radius);--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-card-cap-padding-y: .5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: rgba(var(--bs-body-color-rgb), 0.03);--bs-card-cap-color: ;--bs-card-height: ;--bs-card-color: ;--bs-card-bg: var(--bs-body-bg);--bs-card-img-overlay-padding: 1rem;--bs-card-group-margin: .75rem;position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0}.card>.list-group:last-child{border-bottom-width:0}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-.5 * var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header-tabs{margin-right:calc(-.5 * var(--bs-card-cap-padding-x));margin-bottom:calc(-1 * var(--bs-card-cap-padding-y));margin-left:calc(-.5 * var(--bs-card-cap-padding-x));border-bottom:0}.card-header-tabs .nav-link.active{background-color:var(--bs-card-bg);border-bottom-color:var(--bs-card-bg)}.card-header-pills{margin-right:calc(-.5 * var(--bs-card-cap-padding-x));margin-left:calc(-.5 * var(--bs-card-cap-padding-x))}.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:var(--bs-card-img-overlay-padding)}.card-img,.card-img-top,.card-img-bottom{width:100%}.card-group>.card{margin-bottom:var(--bs-card-group-margin)}@media (min-width: 576px){.card-group{display:flex;display:-webkit-flex;flex-flow:row wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}}.accordion{--bs-accordion-color: var(--bs-body-color);--bs-accordion-bg: var(--bs-body-bg);--bs-accordion-transition: color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out,border-radius 0.15s ease;--bs-accordion-border-color: var(--bs-border-color);--bs-accordion-border-width: var(--bs-border-width);--bs-accordion-border-radius: var(--bs-border-radius);--bs-accordion-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: var(--bs-body-color);--bs-accordion-btn-bg: var(--bs-accordion-bg);--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23373a3c'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23424242'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #d3d3d3;--bs-accordion-btn-focus-box-shadow: 0 0 0 .25rem rgba(166,166,166,0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: var(--bs-primary-text-emphasis);--bs-accordion-active-bg: var(--bs-primary-bg-subtle)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media (prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1 * var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media (prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:not(:first-of-type){border-top:0}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}[data-bs-theme="dark"] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23cacaca'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23cacaca'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: .5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, "/") /* rtl: var(--bs-breadcrumb-divider, "/") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: .75rem;--bs-pagination-padding-y: .375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: var(--bs-link-color);--bs-pagination-bg: var(--bs-body-bg);--bs-pagination-border-width: var(--bs-border-width);--bs-pagination-border-color: var(--bs-border-color);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: var(--bs-link-hover-color);--bs-pagination-hover-bg: var(--bs-tertiary-bg);--bs-pagination-hover-border-color: var(--bs-border-color);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 .25rem rgba(166,166,166,0.25);--bs-pagination-active-color: #000;--bs-pagination-active-bg: #A6A6A6;--bs-pagination-active-border-color: #A6A6A6;--bs-pagination-disabled-color: var(--bs-secondary-color);--bs-pagination-disabled-bg: var(--bs-secondary-bg);--bs-pagination-disabled-border-color: var(--bs-border-color);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(var(--bs-border-width) * -1)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: .75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: .5rem;--bs-pagination-padding-y: .25rem;--bs-pagination-font-size:.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: .65em;--bs-badge-padding-y: .35em;--bs-badge-font-size:.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 0 solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:.5rem}}.progress,.progress-stacked{--bs-progress-height: .5rem;--bs-progress-font-size:.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #A6A6A6;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media (prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media (prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: .5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-tertiary-bg);--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: var(--bs-body-bg);--bs-list-group-active-color: #000;--bs-list-group-active-bg: #A6A6A6;--bs-list-group-active-border-color: #A6A6A6;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1 * var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media (min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: .5;--bs-btn-close-hover-opacity: .75;--bs-btn-close-focus-shadow: 0 0 0 .25rem rgba(166,166,166,0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: .25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:transparent var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme="dark"] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: .75rem;--bs-toast-padding-y: .5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(var(--bs-body-bg-rgb), 0.85);--bs-toast-border-width: var(--bs-border-width);--bs-toast-border-color: var(--bs-border-color-translucent);--bs-toast-border-radius: var(--bs-border-radius);--bs-toast-box-shadow: var(--bs-box-shadow);--bs-toast-header-color: var(--bs-secondary-color);--bs-toast-header-bg: rgba(var(--bs-body-bg-rgb), 0.85);--bs-toast-header-border-color: var(--bs-border-color-translucent);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 1090;position:absolute;z-index:var(--bs-toast-zindex);width:max-content;width:-webkit-max-content;width:-moz-max-content;width:-ms-max-content;width:-o-max-content;max-width:100%;pointer-events:none}.toast-container>:not(:last-child){margin-bottom:var(--bs-toast-spacing)}.toast-header{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;padding:var(--bs-toast-padding-y) var(--bs-toast-padding-x);color:var(--bs-toast-header-color);background-color:var(--bs-toast-header-bg);background-clip:padding-box;border-bottom:var(--bs-toast-border-width) solid var(--bs-toast-header-border-color)}.toast-header .btn-close{margin-right:calc(-.5 * var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: .5rem;--bs-modal-color: ;--bs-modal-bg: var(--bs-body-bg);--bs-modal-border-color: var(--bs-border-color-translucent);--bs-modal-border-width: var(--bs-border-width);--bs-modal-border-radius: var(--bs-border-radius-lg);--bs-modal-box-shadow: 0 0.125rem 0.25rem rgba(0,0,0,0.075);--bs-modal-inner-border-radius: calc(var(--bs-border-radius-lg) - (var(--bs-border-width)));--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: var(--bs-border-color);--bs-modal-header-border-width: var(--bs-border-width);--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: .5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: var(--bs-border-color);--bs-modal-footer-border-width: var(--bs-border-width);position:fixed;top:0;left:0;z-index:var(--bs-modal-zindex);display:none;width:100%;height:100%;overflow-x:hidden;overflow-y:auto;outline:0}.modal-dialog{position:relative;width:auto;margin:var(--bs-modal-margin);pointer-events:none}.modal.fade .modal-dialog{transition:transform 0.3s 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auto}.btn-group>.btn-check:checked+.btn,.btn-group>.btn-check:focus+.btn,.btn-group>.btn:hover,.btn-group>.btn:focus,.btn-group>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn-check:checked+.btn,.btn-group-vertical>.btn-check:focus+.btn,.btn-group-vertical>.btn:hover,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn.active{z-index:1}.btn-toolbar{display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;justify-content:flex-start;-webkit-justify-content:flex-start}.btn-toolbar .input-group{width:auto}.btn-group>:not(.btn-check:first-child)+.btn,.btn-group>.btn-group:not(:first-child){margin-left:calc(var(--bs-border-width) * -1)}.dropdown-toggle-split{padding-right:.5625rem;padding-left:.5625rem}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;-webkit-flex-direction:column;align-items:flex-start;-webkit-align-items:flex-start;justify-content:center;-webkit-justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(var(--bs-border-width) * -1)}.nav{--bs-nav-link-padding-x: 1rem;--bs-nav-link-padding-y: .5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: var(--bs-link-color);--bs-nav-link-hover-color: var(--bs-link-hover-color);--bs-nav-link-disabled-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem rgba(166,166,166,0.25)}.nav-link.disabled,.nav-link:disabled{color:var(--bs-nav-link-disabled-color);pointer-events:none;cursor:default}.nav-tabs{--bs-nav-tabs-border-width: 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.show>.nav-link{font-weight:700;color:var(--bs-nav-underline-link-active-color);border-bottom-color:currentcolor}.nav-fill>.nav-link,.nav-fill .nav-item{flex:1 1 auto;-webkit-flex:1 1 auto;text-align:center}.nav-justified>.nav-link,.nav-justified .nav-item{flex-basis:0;-webkit-flex-basis:0;flex-grow:1;-webkit-flex-grow:1;text-align:center}.nav-fill .nav-item .nav-link,.nav-justified .nav-item .nav-link{width:100%}.tab-content>.tab-pane{display:none}.tab-content>.active{display:block}.navbar{--bs-navbar-padding-x: 0;--bs-navbar-padding-y: .5rem;--bs-navbar-color: rgba(255,255,255,0.65);--bs-navbar-hover-color: rgba(0,0,0,0.9);--bs-navbar-disabled-color: rgba(255,255,255,0.3);--bs-navbar-active-color: #fff;--bs-navbar-brand-padding-y: .3125rem;--bs-navbar-brand-margin-end: 1rem;--bs-navbar-brand-font-size: 1.25rem;--bs-navbar-brand-color: #fff;--bs-navbar-brand-hover-color: #fff;--bs-navbar-nav-link-padding-x: .5rem;--bs-navbar-toggler-padding-y: .25rem;--bs-navbar-toggler-padding-x: .75rem;--bs-navbar-toggler-font-size: 1.25rem;--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e");--bs-navbar-toggler-border-color: rgba(255,255,255,0.15);--bs-navbar-toggler-border-radius: var(--bs-border-radius);--bs-navbar-toggler-focus-width: .25rem;--bs-navbar-toggler-transition: box-shadow 0.15s ease-in-out;position:relative;display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;align-items:center;-webkit-align-items:center;justify-content:space-between;-webkit-justify-content:space-between;padding:var(--bs-navbar-padding-y) 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var(--bs-navbar-hover-color);--bs-nav-link-disabled-color: var(--bs-navbar-disabled-color);display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;list-style:none}.navbar-nav .nav-link.active,.navbar-nav .nav-link.show{color:var(--bs-navbar-active-color)}.navbar-nav .dropdown-menu{position:static}.navbar-text{padding-top:.5rem;padding-bottom:.5rem;color:var(--bs-navbar-color)}.navbar-text a,.navbar-text a:hover,.navbar-text a:focus{color:var(--bs-navbar-active-color)}.navbar-collapse{flex-basis:100%;-webkit-flex-basis:100%;flex-grow:1;-webkit-flex-grow:1;align-items:center;-webkit-align-items:center}.navbar-toggler{padding:var(--bs-navbar-toggler-padding-y) var(--bs-navbar-toggler-padding-x);font-size:var(--bs-navbar-toggler-font-size);line-height:1;color:var(--bs-navbar-color);background-color:transparent;border:var(--bs-border-width) solid 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992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas 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0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #d3d3d3;--bs-accordion-btn-focus-box-shadow: 0 0 0 .25rem rgba(166,166,166,0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: var(--bs-primary-text-emphasis);--bs-accordion-active-bg: var(--bs-primary-bg-subtle)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media (prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1 * var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media (prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:not(:first-of-type){border-top:0}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}[data-bs-theme="dark"] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23cacaca'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23cacaca'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: .5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, "/") /* rtl: var(--bs-breadcrumb-divider, "/") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: .75rem;--bs-pagination-padding-y: .375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: var(--bs-link-color);--bs-pagination-bg: var(--bs-body-bg);--bs-pagination-border-width: var(--bs-border-width);--bs-pagination-border-color: var(--bs-border-color);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: var(--bs-link-hover-color);--bs-pagination-hover-bg: var(--bs-tertiary-bg);--bs-pagination-hover-border-color: var(--bs-border-color);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 .25rem rgba(166,166,166,0.25);--bs-pagination-active-color: #000;--bs-pagination-active-bg: #A6A6A6;--bs-pagination-active-border-color: #A6A6A6;--bs-pagination-disabled-color: var(--bs-secondary-color);--bs-pagination-disabled-bg: var(--bs-secondary-bg);--bs-pagination-disabled-border-color: var(--bs-border-color);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(var(--bs-border-width) * -1)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: .75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: .5rem;--bs-pagination-padding-y: .25rem;--bs-pagination-font-size:.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: .65em;--bs-badge-padding-y: .35em;--bs-badge-font-size:.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 0 solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:.5rem}}.progress,.progress-stacked{--bs-progress-height: .5rem;--bs-progress-font-size:.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #A6A6A6;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media (prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media (prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: .5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-tertiary-bg);--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: var(--bs-body-bg);--bs-list-group-active-color: #000;--bs-list-group-active-bg: #A6A6A6;--bs-list-group-active-border-color: #A6A6A6;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1 * var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media (min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: .5;--bs-btn-close-hover-opacity: .75;--bs-btn-close-focus-shadow: 0 0 0 .25rem rgba(166,166,166,0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: .25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:transparent var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme="dark"] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: .75rem;--bs-toast-padding-y: .5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(var(--bs-body-bg-rgb), 0.85);--bs-toast-border-width: var(--bs-border-width);--bs-toast-border-color: var(--bs-border-color-translucent);--bs-toast-border-radius: var(--bs-border-radius);--bs-toast-box-shadow: var(--bs-box-shadow);--bs-toast-header-color: var(--bs-secondary-color);--bs-toast-header-bg: rgba(var(--bs-body-bg-rgb), 0.85);--bs-toast-header-border-color: var(--bs-border-color-translucent);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 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calc(var(--bs-tooltip-arrow-width) * .5) 0;border-top-color:var(--bs-tooltip-bg)}.bs-tooltip-end .tooltip-arrow,.bs-tooltip-auto[data-popper-placement^="right"] .tooltip-arrow{left:calc(-1 * var(--bs-tooltip-arrow-height));width:var(--bs-tooltip-arrow-height);height:var(--bs-tooltip-arrow-width)}.bs-tooltip-end .tooltip-arrow::before,.bs-tooltip-auto[data-popper-placement^="right"] .tooltip-arrow::before{right:-1px;border-width:calc(var(--bs-tooltip-arrow-width) * .5) var(--bs-tooltip-arrow-height) calc(var(--bs-tooltip-arrow-width) * .5) 0;border-right-color:var(--bs-tooltip-bg)}.bs-tooltip-bottom .tooltip-arrow,.bs-tooltip-auto[data-popper-placement^="bottom"] .tooltip-arrow{top:calc(-1 * var(--bs-tooltip-arrow-height))}.bs-tooltip-bottom .tooltip-arrow::before,.bs-tooltip-auto[data-popper-placement^="bottom"] .tooltip-arrow::before{bottom:-1px;border-width:0 calc(var(--bs-tooltip-arrow-width) * .5) 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diff --git a/deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js b/deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js
new file mode 100644
index 00000000..c628326a
--- /dev/null
+++ b/deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js
@@ -0,0 +1,5 @@
+/*!
+ * Bootstrap Table of Contents v1.0.1 (http://afeld.github.io/bootstrap-toc/)
+ * Copyright 2015 Aidan Feldman
+ * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
+!function(a){"use strict";window.Toc={helpers:{findOrFilter:function(e,t){var n=e.find(t);return e.filter(t).add(n).filter(":not([data-toc-skip])")},generateUniqueIdBase:function(e){return a(e).text().trim().replace(/\'/gi,"").replace(/[& +$,:;=?@"#{}|^~[`%!'<>\]\.\/\(\)\*\\\n\t\b\v]/g,"-").replace(/-{2,}/g,"-").substring(0,64).replace(/^-+|-+$/gm,"").toLowerCase()||e.tagName.toLowerCase()},generateUniqueId:function(e){for(var t=this.generateUniqueIdBase(e),n=0;;n++){var r=t;if(0<n&&(r+="-"+n),!document.getElementById(r))return r}},generateAnchor:function(e){if(e.id)return e.id;var t=this.generateUniqueId(e);return e.id=t},createNavList:function(){return a('<ul class="nav navbar-nav"></ul>')},createChildNavList:function(e){var t=this.createNavList();return e.append(t),t},generateNavEl:function(e,t){var n=a('<a class="nav-link"></a>');n.attr("href","#"+e),n.text(t);var r=a("<li></li>");return r.append(n),r},generateNavItem:function(e){var t=this.generateAnchor(e),n=a(e),r=n.data("toc-text")||n.text();return this.generateNavEl(t,r)},getTopLevel:function(e){for(var t=1;t<=6;t++){if(1<this.findOrFilter(e,"h"+t).length)return t}return 1},getHeadings:function(e,t){var n="h"+t,r="h"+(t+1);return this.findOrFilter(e,n+","+r)},getNavLevel:function(e){return parseInt(e.tagName.charAt(1),10)},populateNav:function(r,a,e){var i,s=r,c=this;e.each(function(e,t){var n=c.generateNavItem(t);c.getNavLevel(t)===a?s=r:i&&s===r&&(s=c.createChildNavList(i)),s.append(n),i=n})},parseOps:function(e){var t;return(t=e.jquery?{$nav:e}:e).$scope=t.$scope||a(document.body),t}},init:function(e){(e=this.helpers.parseOps(e)).$nav.attr("data-toggle","toc");var t=this.helpers.createChildNavList(e.$nav),n=this.helpers.getTopLevel(e.$scope),r=this.helpers.getHeadings(e.$scope,n);this.helpers.populateNav(t,n,r)}},a(function(){a('nav[data-toggle="toc"]').each(function(e,t){var n=a(t);Toc.init(n)})})}(jQuery);
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new file mode 100644
index 00000000..1103f811
--- /dev/null
+++ b/deps/clipboard.js-2.0.11/clipboard.min.js
@@ -0,0 +1,7 @@
+/*!
+ * clipboard.js v2.0.11
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
+!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return b}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),r=n.n(e);function c(t){try{return document.execCommand(t)}catch(t){return}}var a=function(t){t=r()(t);return c("cut"),t};function o(t,e){var n,o,t=(n=t,o="rtl"===document.documentElement.getAttribute("dir"),(t=document.createElement("textarea")).style.fontSize="12pt",t.style.border="0",t.style.padding="0",t.style.margin="0",t.style.position="absolute",t.style[o?"right":"left"]="-9999px",o=window.pageYOffset||document.documentElement.scrollTop,t.style.top="".concat(o,"px"),t.setAttribute("readonly",""),t.value=n,t);return e.container.appendChild(t),e=r()(t),c("copy"),t.remove(),e}var f=function(t){var e=1<arguments.length&&void 0!==arguments[1]?arguments[1]:{container:document.body},n="";return"string"==typeof t?n=o(t,e):t instanceof HTMLInputElement&&!["text","search","url","tel","password"].includes(null==t?void 0:t.type)?n=o(t.value,e):(n=r()(t),c("copy")),n};function l(t){return(l="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}var s=function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:{},e=t.action,n=void 0===e?"copy":e,o=t.container,e=t.target,t=t.text;if("copy"!==n&&"cut"!==n)throw new Error('Invalid "action" value, use either "copy" or "cut"');if(void 0!==e){if(!e||"object"!==l(e)||1!==e.nodeType)throw new Error('Invalid "target" value, use a valid Element');if("copy"===n&&e.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. 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t=o?(t=v(this).constructor,Reflect.construct(e,arguments,t)):e.apply(this,arguments),e=this,!(t=t)||"object"!==p(t)&&"function"!=typeof t?function(t){if(void 0!==t)return t;throw new ReferenceError("this hasn't been initialised - super() hasn't been called")}(e):t}}function v(t){return(v=Object.setPrototypeOf?Object.getPrototypeOf:function(t){return t.__proto__||Object.getPrototypeOf(t)})(t)}function m(t,e){t="data-clipboard-".concat(t);if(e.hasAttribute(t))return e.getAttribute(t)}var b=function(){!function(t,e){if("function"!=typeof e&&null!==e)throw new TypeError("Super expression must either be null or a function");t.prototype=Object.create(e&&e.prototype,{constructor:{value:t,writable:!0,configurable:!0}}),e&&y(t,e)}(r,i());var t,e,n,o=h(r);function r(t,e){var n;return function(t){if(!(t instanceof r))throw new TypeError("Cannot call a class as a function")}(this),(n=o.call(this)).resolveOptions(e),n.listenClick(t),n}return t=r,n=[{key:"copy",value:function(t){var e=1<arguments.length&&void 0!==arguments[1]?arguments[1]:{container:document.body};return f(t,e)}},{key:"cut",value:function(t){return a(t)}},{key:"isSupported",value:function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:["copy","cut"],t="string"==typeof t?[t]:t,e=!!document.queryCommandSupported;return t.forEach(function(t){e=e&&!!document.queryCommandSupported(t)}),e}}],(e=[{key:"resolveOptions",value:function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:{};this.action="function"==typeof t.action?t.action:this.defaultAction,this.target="function"==typeof t.target?t.target:this.defaultTarget,this.text="function"==typeof t.text?t.text:this.defaultText,this.container="object"===p(t.container)?t.container:document.body}},{key:"listenClick",value:function(t){var e=this;this.listener=u()(t,"click",function(t){return e.onClick(t)})}},{key:"onClick",value:function(t){var e=t.delegateTarget||t.currentTarget,n=this.action(e)||"copy",t=s({action:n,container:this.container,target:this.target(e),text:this.text(e)});this.emit(t?"success":"error",{action:n,text:t,trigger:e,clearSelection:function(){e&&e.focus(),window.getSelection().removeAllRanges()}})}},{key:"defaultAction",value:function(t){return m("action",t)}},{key:"defaultTarget",value:function(t){t=m("target",t);if(t)return document.querySelector(t)}},{key:"defaultText",value:function(t){return m("text",t)}},{key:"destroy",value:function(){this.listener.destroy()}}])&&d(t.prototype,e),n&&d(t,n),r}()},828:function(t){var e;"undefined"==typeof Element||Element.prototype.matches||((e=Element.prototype).matches=e.matchesSelector||e.mozMatchesSelector||e.msMatchesSelector||e.oMatchesSelector||e.webkitMatchesSelector),t.exports=function(t,e){for(;t&&9!==t.nodeType;){if("function"==typeof t.matches&&t.matches(e))return t;t=t.parentNode}}},438:function(t,e,n){var u=n(828);function i(t,e,n,o,r){var 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e,n="SELECT"===t.nodeName?(t.focus(),t.value):"INPUT"===t.nodeName||"TEXTAREA"===t.nodeName?((e=t.hasAttribute("readonly"))||t.setAttribute("readonly",""),t.select(),t.setSelectionRange(0,t.value.length),e||t.removeAttribute("readonly"),t.value):(t.hasAttribute("contenteditable")&&t.focus(),n=window.getSelection(),(e=document.createRange()).selectNodeContents(t),n.removeAllRanges(),n.addRange(e),n.toString());return n}},279:function(t){function e(){}e.prototype={on:function(t,e,n){var o=this.e||(this.e={});return(o[t]||(o[t]=[])).push({fn:e,ctx:n}),this},once:function(t,e,n){var o=this;function r(){o.off(t,r),e.apply(n,arguments)}return r._=e,this.on(t,r,n)},emit:function(t){for(var e=[].slice.call(arguments,1),n=((this.e||(this.e={}))[t]||[]).slice(),o=0,r=n.length;o<r;o++)n[o].fn.apply(n[o].ctx,e);return this},off:function(t,e){var n=this.e||(this.e={}),o=n[t],r=[];if(o&&e)for(var i=0,u=o.length;i<u;i++)o[i].fn!==e&&o[i].fn._!==e&&r.push(o[i]);return r.length?n[t]=r:delete 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\ No newline at end of file
diff --git a/deps/data-deps.txt b/deps/data-deps.txt
index 693b82d1..8aa49e21 100644
--- a/deps/data-deps.txt
+++ b/deps/data-deps.txt
@@ -2,3 +2,12 @@
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no" />
 <link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet" />
 <script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script>
+<link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet" />
+<script src="deps/headroom-0.11.0/headroom.min.js"></script>
+<script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script>
+<script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script>
+<script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script>
+<script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script>
+<script src="deps/search-1.0.0/fuse.min.js"></script>
+<script src="deps/search-1.0.0/mark.min.js"></script>
diff --git a/deps/font-awesome-6.4.2/css/all.css b/deps/font-awesome-6.4.2/css/all.css
new file mode 100644
index 00000000..bdb6e3ae
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/all.css
@@ -0,0 +1,7968 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa {
+  font-family: var(--fa-style-family, "Font Awesome 6 Free");
+  font-weight: var(--fa-style, 900); }
+
+.fa,
+.fa-classic,
+.fa-sharp,
+.fas,
+.fa-solid,
+.far,
+.fa-regular,
+.fab,
+.fa-brands {
+  -moz-osx-font-smoothing: grayscale;
+  -webkit-font-smoothing: antialiased;
+  display: var(--fa-display, inline-block);
+  font-style: normal;
+  font-variant: normal;
+  line-height: 1;
+  text-rendering: auto; }
+
+.fas,
+.fa-classic,
+.fa-solid,
+.far,
+.fa-regular {
+  font-family: 'Font Awesome 6 Free'; }
+
+.fab,
+.fa-brands {
+  font-family: 'Font Awesome 6 Brands'; }
+
+.fa-1x {
+  font-size: 1em; }
+
+.fa-2x {
+  font-size: 2em; }
+
+.fa-3x {
+  font-size: 3em; }
+
+.fa-4x {
+  font-size: 4em; }
+
+.fa-5x {
+  font-size: 5em; }
+
+.fa-6x {
+  font-size: 6em; }
+
+.fa-7x {
+  font-size: 7em; }
+
+.fa-8x {
+  font-size: 8em; }
+
+.fa-9x {
+  font-size: 9em; }
+
+.fa-10x {
+  font-size: 10em; }
+
+.fa-2xs {
+  font-size: 0.625em;
+  line-height: 0.1em;
+  vertical-align: 0.225em; }
+
+.fa-xs {
+  font-size: 0.75em;
+  line-height: 0.08333em;
+  vertical-align: 0.125em; }
+
+.fa-sm {
+  font-size: 0.875em;
+  line-height: 0.07143em;
+  vertical-align: 0.05357em; }
+
+.fa-lg {
+  font-size: 1.25em;
+  line-height: 0.05em;
+  vertical-align: -0.075em; }
+
+.fa-xl {
+  font-size: 1.5em;
+  line-height: 0.04167em;
+  vertical-align: -0.125em; }
+
+.fa-2xl {
+  font-size: 2em;
+  line-height: 0.03125em;
+  vertical-align: -0.1875em; }
+
+.fa-fw {
+  text-align: center;
+  width: 1.25em; }
+
+.fa-ul {
+  list-style-type: none;
+  margin-left: var(--fa-li-margin, 2.5em);
+  padding-left: 0; }
+  .fa-ul > li {
+    position: relative; }
+
+.fa-li {
+  left: calc(var(--fa-li-width, 2em) * -1);
+  position: absolute;
+  text-align: center;
+  width: var(--fa-li-width, 2em);
+  line-height: inherit; }
+
+.fa-border {
+  border-color: var(--fa-border-color, #eee);
+  border-radius: var(--fa-border-radius, 0.1em);
+  border-style: var(--fa-border-style, solid);
+  border-width: var(--fa-border-width, 0.08em);
+  padding: var(--fa-border-padding, 0.2em 0.25em 0.15em); }
+
+.fa-pull-left {
+  float: left;
+  margin-right: var(--fa-pull-margin, 0.3em); }
+
+.fa-pull-right {
+  float: right;
+  margin-left: var(--fa-pull-margin, 0.3em); }
+
+.fa-beat {
+  -webkit-animation-name: fa-beat;
+          animation-name: fa-beat;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-bounce {
+  -webkit-animation-name: fa-bounce;
+          animation-name: fa-bounce;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); }
+
+.fa-fade {
+  -webkit-animation-name: fa-fade;
+          animation-name: fa-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-beat-fade {
+  -webkit-animation-name: fa-beat-fade;
+          animation-name: fa-beat-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-flip {
+  -webkit-animation-name: fa-flip;
+          animation-name: fa-flip;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-shake {
+  -webkit-animation-name: fa-shake;
+          animation-name: fa-shake;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 2s);
+          animation-duration: var(--fa-animation-duration, 2s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin-reverse {
+  --fa-animation-direction: reverse; }
+
+.fa-pulse,
+.fa-spin-pulse {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, steps(8));
+          animation-timing-function: var(--fa-animation-timing, steps(8)); }
+
+@media (prefers-reduced-motion: reduce) {
+  .fa-beat,
+  .fa-bounce,
+  .fa-fade,
+  .fa-beat-fade,
+  .fa-flip,
+  .fa-pulse,
+  .fa-shake,
+  .fa-spin,
+  .fa-spin-pulse {
+    -webkit-animation-delay: -1ms;
+            animation-delay: -1ms;
+    -webkit-animation-duration: 1ms;
+            animation-duration: 1ms;
+    -webkit-animation-iteration-count: 1;
+            animation-iteration-count: 1;
+    -webkit-transition-delay: 0s;
+            transition-delay: 0s;
+    -webkit-transition-duration: 0s;
+            transition-duration: 0s; } }
+
+@-webkit-keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@-webkit-keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@-webkit-keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@-webkit-keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@-webkit-keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@-webkit-keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@-webkit-keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+  -webkit-transform: rotate(90deg);
+          transform: rotate(90deg); }
+
+.fa-rotate-180 {
+  -webkit-transform: rotate(180deg);
+          transform: rotate(180deg); }
+
+.fa-rotate-270 {
+  -webkit-transform: rotate(270deg);
+          transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+  -webkit-transform: scale(-1, 1);
+          transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+  -webkit-transform: scale(1, -1);
+          transform: scale(1, -1); }
+
+.fa-flip-both,
+.fa-flip-horizontal.fa-flip-vertical {
+  -webkit-transform: scale(-1, -1);
+          transform: scale(-1, -1); }
+
+.fa-rotate-by {
+  -webkit-transform: rotate(var(--fa-rotate-angle, none));
+          transform: rotate(var(--fa-rotate-angle, none)); }
+
+.fa-stack {
+  display: inline-block;
+  height: 2em;
+  line-height: 2em;
+  position: relative;
+  vertical-align: middle;
+  width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+  left: 0;
+  position: absolute;
+  text-align: center;
+  width: 100%;
+  z-index: var(--fa-stack-z-index, auto); }
+
+.fa-stack-1x {
+  line-height: inherit; }
+
+.fa-stack-2x {
+  font-size: 2em; }
+
+.fa-inverse {
+  color: var(--fa-inverse, #fff); }
+
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+readers do not read off random characters that represent icons */
+
+.fa-0::before {
+  content: "\30"; }
+
+.fa-1::before {
+  content: "\31"; }
+
+.fa-2::before {
+  content: "\32"; }
+
+.fa-3::before {
+  content: "\33"; }
+
+.fa-4::before {
+  content: "\34"; }
+
+.fa-5::before {
+  content: "\35"; }
+
+.fa-6::before {
+  content: "\36"; }
+
+.fa-7::before {
+  content: "\37"; }
+
+.fa-8::before {
+  content: "\38"; }
+
+.fa-9::before {
+  content: "\39"; }
+
+.fa-fill-drip::before {
+  content: "\f576"; }
+
+.fa-arrows-to-circle::before {
+  content: "\e4bd"; }
+
+.fa-circle-chevron-right::before {
+  content: "\f138"; }
+
+.fa-chevron-circle-right::before {
+  content: "\f138"; }
+
+.fa-at::before {
+  content: "\40"; }
+
+.fa-trash-can::before {
+  content: "\f2ed"; }
+
+.fa-trash-alt::before {
+  content: "\f2ed"; }
+
+.fa-text-height::before {
+  content: "\f034"; }
+
+.fa-user-xmark::before {
+  content: "\f235"; }
+
+.fa-user-times::before {
+  content: "\f235"; }
+
+.fa-stethoscope::before {
+  content: "\f0f1"; }
+
+.fa-message::before {
+  content: "\f27a"; }
+
+.fa-comment-alt::before {
+  content: "\f27a"; }
+
+.fa-info::before {
+  content: "\f129"; }
+
+.fa-down-left-and-up-right-to-center::before {
+  content: "\f422"; }
+
+.fa-compress-alt::before {
+  content: "\f422"; }
+
+.fa-explosion::before {
+  content: "\e4e9"; }
+
+.fa-file-lines::before {
+  content: "\f15c"; }
+
+.fa-file-alt::before {
+  content: "\f15c"; }
+
+.fa-file-text::before {
+  content: "\f15c"; }
+
+.fa-wave-square::before {
+  content: "\f83e"; }
+
+.fa-ring::before {
+  content: "\f70b"; }
+
+.fa-building-un::before {
+  content: "\e4d9"; }
+
+.fa-dice-three::before {
+  content: "\f527"; }
+
+.fa-calendar-days::before {
+  content: "\f073"; }
+
+.fa-calendar-alt::before {
+  content: "\f073"; }
+
+.fa-anchor-circle-check::before {
+  content: "\e4aa"; }
+
+.fa-building-circle-arrow-right::before {
+  content: "\e4d1"; }
+
+.fa-volleyball::before {
+  content: "\f45f"; }
+
+.fa-volleyball-ball::before {
+  content: "\f45f"; }
+
+.fa-arrows-up-to-line::before {
+  content: "\e4c2"; }
+
+.fa-sort-down::before {
+  content: "\f0dd"; }
+
+.fa-sort-desc::before {
+  content: "\f0dd"; }
+
+.fa-circle-minus::before {
+  content: "\f056"; }
+
+.fa-minus-circle::before {
+  content: "\f056"; }
+
+.fa-door-open::before {
+  content: "\f52b"; }
+
+.fa-right-from-bracket::before {
+  content: "\f2f5"; }
+
+.fa-sign-out-alt::before {
+  content: "\f2f5"; }
+
+.fa-atom::before {
+  content: "\f5d2"; }
+
+.fa-soap::before {
+  content: "\e06e"; }
+
+.fa-icons::before {
+  content: "\f86d"; }
+
+.fa-heart-music-camera-bolt::before {
+  content: "\f86d"; }
+
+.fa-microphone-lines-slash::before {
+  content: "\f539"; }
+
+.fa-microphone-alt-slash::before {
+  content: "\f539"; }
+
+.fa-bridge-circle-check::before {
+  content: "\e4c9"; }
+
+.fa-pump-medical::before {
+  content: "\e06a"; }
+
+.fa-fingerprint::before {
+  content: "\f577"; }
+
+.fa-hand-point-right::before {
+  content: "\f0a4"; }
+
+.fa-magnifying-glass-location::before {
+  content: "\f689"; }
+
+.fa-search-location::before {
+  content: "\f689"; }
+
+.fa-forward-step::before {
+  content: "\f051"; }
+
+.fa-step-forward::before {
+  content: "\f051"; }
+
+.fa-face-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-flag-checkered::before {
+  content: "\f11e"; }
+
+.fa-football::before {
+  content: "\f44e"; }
+
+.fa-football-ball::before {
+  content: "\f44e"; }
+
+.fa-school-circle-exclamation::before {
+  content: "\e56c"; }
+
+.fa-crop::before {
+  content: "\f125"; }
+
+.fa-angles-down::before {
+  content: "\f103"; }
+
+.fa-angle-double-down::before {
+  content: "\f103"; }
+
+.fa-users-rectangle::before {
+  content: "\e594"; }
+
+.fa-people-roof::before {
+  content: "\e537"; }
+
+.fa-people-line::before {
+  content: "\e534"; }
+
+.fa-beer-mug-empty::before {
+  content: "\f0fc"; }
+
+.fa-beer::before {
+  content: "\f0fc"; }
+
+.fa-diagram-predecessor::before {
+  content: "\e477"; }
+
+.fa-arrow-up-long::before {
+  content: "\f176"; }
+
+.fa-long-arrow-up::before {
+  content: "\f176"; }
+
+.fa-fire-flame-simple::before {
+  content: "\f46a"; }
+
+.fa-burn::before {
+  content: "\f46a"; }
+
+.fa-person::before {
+  content: "\f183"; }
+
+.fa-male::before {
+  content: "\f183"; }
+
+.fa-laptop::before {
+  content: "\f109"; }
+
+.fa-file-csv::before {
+  content: "\f6dd"; }
+
+.fa-menorah::before {
+  content: "\f676"; }
+
+.fa-truck-plane::before {
+  content: "\e58f"; }
+
+.fa-record-vinyl::before {
+  content: "\f8d9"; }
+
+.fa-face-grin-stars::before {
+  content: "\f587"; }
+
+.fa-grin-stars::before {
+  content: "\f587"; }
+
+.fa-bong::before {
+  content: "\f55c"; }
+
+.fa-spaghetti-monster-flying::before {
+  content: "\f67b"; }
+
+.fa-pastafarianism::before {
+  content: "\f67b"; }
+
+.fa-arrow-down-up-across-line::before {
+  content: "\e4af"; }
+
+.fa-spoon::before {
+  content: "\f2e5"; }
+
+.fa-utensil-spoon::before {
+  content: "\f2e5"; }
+
+.fa-jar-wheat::before {
+  content: "\e517"; }
+
+.fa-envelopes-bulk::before {
+  content: "\f674"; }
+
+.fa-mail-bulk::before {
+  content: "\f674"; }
+
+.fa-file-circle-exclamation::before {
+  content: "\e4eb"; }
+
+.fa-circle-h::before {
+  content: "\f47e"; }
+
+.fa-hospital-symbol::before {
+  content: "\f47e"; }
+
+.fa-pager::before {
+  content: "\f815"; }
+
+.fa-address-book::before {
+  content: "\f2b9"; }
+
+.fa-contact-book::before {
+  content: "\f2b9"; }
+
+.fa-strikethrough::before {
+  content: "\f0cc"; }
+
+.fa-k::before {
+  content: "\4b"; }
+
+.fa-landmark-flag::before {
+  content: "\e51c"; }
+
+.fa-pencil::before {
+  content: "\f303"; }
+
+.fa-pencil-alt::before {
+  content: "\f303"; }
+
+.fa-backward::before {
+  content: "\f04a"; }
+
+.fa-caret-right::before {
+  content: "\f0da"; }
+
+.fa-comments::before {
+  content: "\f086"; }
+
+.fa-paste::before {
+  content: "\f0ea"; }
+
+.fa-file-clipboard::before {
+  content: "\f0ea"; }
+
+.fa-code-pull-request::before {
+  content: "\e13c"; }
+
+.fa-clipboard-list::before {
+  content: "\f46d"; }
+
+.fa-truck-ramp-box::before {
+  content: "\f4de"; }
+
+.fa-truck-loading::before {
+  content: "\f4de"; }
+
+.fa-user-check::before {
+  content: "\f4fc"; }
+
+.fa-vial-virus::before {
+  content: "\e597"; }
+
+.fa-sheet-plastic::before {
+  content: "\e571"; }
+
+.fa-blog::before {
+  content: "\f781"; }
+
+.fa-user-ninja::before {
+  content: "\f504"; }
+
+.fa-person-arrow-up-from-line::before {
+  content: "\e539"; }
+
+.fa-scroll-torah::before {
+  content: "\f6a0"; }
+
+.fa-torah::before {
+  content: "\f6a0"; }
+
+.fa-broom-ball::before {
+  content: "\f458"; }
+
+.fa-quidditch::before {
+  content: "\f458"; }
+
+.fa-quidditch-broom-ball::before {
+  content: "\f458"; }
+
+.fa-toggle-off::before {
+  content: "\f204"; }
+
+.fa-box-archive::before {
+  content: "\f187"; }
+
+.fa-archive::before {
+  content: "\f187"; }
+
+.fa-person-drowning::before {
+  content: "\e545"; }
+
+.fa-arrow-down-9-1::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-desc::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-down-alt::before {
+  content: "\f886"; }
+
+.fa-face-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-spray-can::before {
+  content: "\f5bd"; }
+
+.fa-truck-monster::before {
+  content: "\f63b"; }
+
+.fa-w::before {
+  content: "\57"; }
+
+.fa-earth-africa::before {
+  content: "\f57c"; }
+
+.fa-globe-africa::before {
+  content: "\f57c"; }
+
+.fa-rainbow::before {
+  content: "\f75b"; }
+
+.fa-circle-notch::before {
+  content: "\f1ce"; }
+
+.fa-tablet-screen-button::before {
+  content: "\f3fa"; }
+
+.fa-tablet-alt::before {
+  content: "\f3fa"; }
+
+.fa-paw::before {
+  content: "\f1b0"; }
+
+.fa-cloud::before {
+  content: "\f0c2"; }
+
+.fa-trowel-bricks::before {
+  content: "\e58a"; }
+
+.fa-face-flushed::before {
+  content: "\f579"; }
+
+.fa-flushed::before {
+  content: "\f579"; }
+
+.fa-hospital-user::before {
+  content: "\f80d"; }
+
+.fa-tent-arrow-left-right::before {
+  content: "\e57f"; }
+
+.fa-gavel::before {
+  content: "\f0e3"; }
+
+.fa-legal::before {
+  content: "\f0e3"; }
+
+.fa-binoculars::before {
+  content: "\f1e5"; }
+
+.fa-microphone-slash::before {
+  content: "\f131"; }
+
+.fa-box-tissue::before {
+  content: "\e05b"; }
+
+.fa-motorcycle::before {
+  content: "\f21c"; }
+
+.fa-bell-concierge::before {
+  content: "\f562"; }
+
+.fa-concierge-bell::before {
+  content: "\f562"; }
+
+.fa-pen-ruler::before {
+  content: "\f5ae"; }
+
+.fa-pencil-ruler::before {
+  content: "\f5ae"; }
+
+.fa-people-arrows::before {
+  content: "\e068"; }
+
+.fa-people-arrows-left-right::before {
+  content: "\e068"; }
+
+.fa-mars-and-venus-burst::before {
+  content: "\e523"; }
+
+.fa-square-caret-right::before {
+  content: "\f152"; }
+
+.fa-caret-square-right::before {
+  content: "\f152"; }
+
+.fa-scissors::before {
+  content: "\f0c4"; }
+
+.fa-cut::before {
+  content: "\f0c4"; }
+
+.fa-sun-plant-wilt::before {
+  content: "\e57a"; }
+
+.fa-toilets-portable::before {
+  content: "\e584"; }
+
+.fa-hockey-puck::before {
+  content: "\f453"; }
+
+.fa-table::before {
+  content: "\f0ce"; }
+
+.fa-magnifying-glass-arrow-right::before {
+  content: "\e521"; }
+
+.fa-tachograph-digital::before {
+  content: "\f566"; }
+
+.fa-digital-tachograph::before {
+  content: "\f566"; }
+
+.fa-users-slash::before {
+  content: "\e073"; }
+
+.fa-clover::before {
+  content: "\e139"; }
+
+.fa-reply::before {
+  content: "\f3e5"; }
+
+.fa-mail-reply::before {
+  content: "\f3e5"; }
+
+.fa-star-and-crescent::before {
+  content: "\f699"; }
+
+.fa-house-fire::before {
+  content: "\e50c"; }
+
+.fa-square-minus::before {
+  content: "\f146"; }
+
+.fa-minus-square::before {
+  content: "\f146"; }
+
+.fa-helicopter::before {
+  content: "\f533"; }
+
+.fa-compass::before {
+  content: "\f14e"; }
+
+.fa-square-caret-down::before {
+  content: "\f150"; }
+
+.fa-caret-square-down::before {
+  content: "\f150"; }
+
+.fa-file-circle-question::before {
+  content: "\e4ef"; }
+
+.fa-laptop-code::before {
+  content: "\f5fc"; }
+
+.fa-swatchbook::before {
+  content: "\f5c3"; }
+
+.fa-prescription-bottle::before {
+  content: "\f485"; }
+
+.fa-bars::before {
+  content: "\f0c9"; }
+
+.fa-navicon::before {
+  content: "\f0c9"; }
+
+.fa-people-group::before {
+  content: "\e533"; }
+
+.fa-hourglass-end::before {
+  content: "\f253"; }
+
+.fa-hourglass-3::before {
+  content: "\f253"; }
+
+.fa-heart-crack::before {
+  content: "\f7a9"; }
+
+.fa-heart-broken::before {
+  content: "\f7a9"; }
+
+.fa-square-up-right::before {
+  content: "\f360"; }
+
+.fa-external-link-square-alt::before {
+  content: "\f360"; }
+
+.fa-face-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-film::before {
+  content: "\f008"; }
+
+.fa-ruler-horizontal::before {
+  content: "\f547"; }
+
+.fa-people-robbery::before {
+  content: "\e536"; }
+
+.fa-lightbulb::before {
+  content: "\f0eb"; }
+
+.fa-caret-left::before {
+  content: "\f0d9"; }
+
+.fa-circle-exclamation::before {
+  content: "\f06a"; }
+
+.fa-exclamation-circle::before {
+  content: "\f06a"; }
+
+.fa-school-circle-xmark::before {
+  content: "\e56d"; }
+
+.fa-arrow-right-from-bracket::before {
+  content: "\f08b"; }
+
+.fa-sign-out::before {
+  content: "\f08b"; }
+
+.fa-circle-chevron-down::before {
+  content: "\f13a"; }
+
+.fa-chevron-circle-down::before {
+  content: "\f13a"; }
+
+.fa-unlock-keyhole::before {
+  content: "\f13e"; }
+
+.fa-unlock-alt::before {
+  content: "\f13e"; }
+
+.fa-cloud-showers-heavy::before {
+  content: "\f740"; }
+
+.fa-headphones-simple::before {
+  content: "\f58f"; }
+
+.fa-headphones-alt::before {
+  content: "\f58f"; }
+
+.fa-sitemap::before {
+  content: "\f0e8"; }
+
+.fa-circle-dollar-to-slot::before {
+  content: "\f4b9"; }
+
+.fa-donate::before {
+  content: "\f4b9"; }
+
+.fa-memory::before {
+  content: "\f538"; }
+
+.fa-road-spikes::before {
+  content: "\e568"; }
+
+.fa-fire-burner::before {
+  content: "\e4f1"; }
+
+.fa-flag::before {
+  content: "\f024"; }
+
+.fa-hanukiah::before {
+  content: "\f6e6"; }
+
+.fa-feather::before {
+  content: "\f52d"; }
+
+.fa-volume-low::before {
+  content: "\f027"; }
+
+.fa-volume-down::before {
+  content: "\f027"; }
+
+.fa-comment-slash::before {
+  content: "\f4b3"; }
+
+.fa-cloud-sun-rain::before {
+  content: "\f743"; }
+
+.fa-compress::before {
+  content: "\f066"; }
+
+.fa-wheat-awn::before {
+  content: "\e2cd"; }
+
+.fa-wheat-alt::before {
+  content: "\e2cd"; }
+
+.fa-ankh::before {
+  content: "\f644"; }
+
+.fa-hands-holding-child::before {
+  content: "\e4fa"; }
+
+.fa-asterisk::before {
+  content: "\2a"; }
+
+.fa-square-check::before {
+  content: "\f14a"; }
+
+.fa-check-square::before {
+  content: "\f14a"; }
+
+.fa-peseta-sign::before {
+  content: "\e221"; }
+
+.fa-heading::before {
+  content: "\f1dc"; }
+
+.fa-header::before {
+  content: "\f1dc"; }
+
+.fa-ghost::before {
+  content: "\f6e2"; }
+
+.fa-list::before {
+  content: "\f03a"; }
+
+.fa-list-squares::before {
+  content: "\f03a"; }
+
+.fa-square-phone-flip::before {
+  content: "\f87b"; }
+
+.fa-phone-square-alt::before {
+  content: "\f87b"; }
+
+.fa-cart-plus::before {
+  content: "\f217"; }
+
+.fa-gamepad::before {
+  content: "\f11b"; }
+
+.fa-circle-dot::before {
+  content: "\f192"; }
+
+.fa-dot-circle::before {
+  content: "\f192"; }
+
+.fa-face-dizzy::before {
+  content: "\f567"; }
+
+.fa-dizzy::before {
+  content: "\f567"; }
+
+.fa-egg::before {
+  content: "\f7fb"; }
+
+.fa-house-medical-circle-xmark::before {
+  content: "\e513"; }
+
+.fa-campground::before {
+  content: "\f6bb"; }
+
+.fa-folder-plus::before {
+  content: "\f65e"; }
+
+.fa-futbol::before {
+  content: "\f1e3"; }
+
+.fa-futbol-ball::before {
+  content: "\f1e3"; }
+
+.fa-soccer-ball::before {
+  content: "\f1e3"; }
+
+.fa-paintbrush::before {
+  content: "\f1fc"; }
+
+.fa-paint-brush::before {
+  content: "\f1fc"; }
+
+.fa-lock::before {
+  content: "\f023"; }
+
+.fa-gas-pump::before {
+  content: "\f52f"; }
+
+.fa-hot-tub-person::before {
+  content: "\f593"; }
+
+.fa-hot-tub::before {
+  content: "\f593"; }
+
+.fa-map-location::before {
+  content: "\f59f"; }
+
+.fa-map-marked::before {
+  content: "\f59f"; }
+
+.fa-house-flood-water::before {
+  content: "\e50e"; }
+
+.fa-tree::before {
+  content: "\f1bb"; }
+
+.fa-bridge-lock::before {
+  content: "\e4cc"; }
+
+.fa-sack-dollar::before {
+  content: "\f81d"; }
+
+.fa-pen-to-square::before {
+  content: "\f044"; }
+
+.fa-edit::before {
+  content: "\f044"; }
+
+.fa-car-side::before {
+  content: "\f5e4"; }
+
+.fa-share-nodes::before {
+  content: "\f1e0"; }
+
+.fa-share-alt::before {
+  content: "\f1e0"; }
+
+.fa-heart-circle-minus::before {
+  content: "\e4ff"; }
+
+.fa-hourglass-half::before {
+  content: "\f252"; }
+
+.fa-hourglass-2::before {
+  content: "\f252"; }
+
+.fa-microscope::before {
+  content: "\f610"; }
+
+.fa-sink::before {
+  content: "\e06d"; }
+
+.fa-bag-shopping::before {
+  content: "\f290"; }
+
+.fa-shopping-bag::before {
+  content: "\f290"; }
+
+.fa-arrow-down-z-a::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-desc::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-down-alt::before {
+  content: "\f881"; }
+
+.fa-mitten::before {
+  content: "\f7b5"; }
+
+.fa-person-rays::before {
+  content: "\e54d"; }
+
+.fa-users::before {
+  content: "\f0c0"; }
+
+.fa-eye-slash::before {
+  content: "\f070"; }
+
+.fa-flask-vial::before {
+  content: "\e4f3"; }
+
+.fa-hand::before {
+  content: "\f256"; }
+
+.fa-hand-paper::before {
+  content: "\f256"; }
+
+.fa-om::before {
+  content: "\f679"; }
+
+.fa-worm::before {
+  content: "\e599"; }
+
+.fa-house-circle-xmark::before {
+  content: "\e50b"; }
+
+.fa-plug::before {
+  content: "\f1e6"; }
+
+.fa-chevron-up::before {
+  content: "\f077"; }
+
+.fa-hand-spock::before {
+  content: "\f259"; }
+
+.fa-stopwatch::before {
+  content: "\f2f2"; }
+
+.fa-face-kiss::before {
+  content: "\f596"; }
+
+.fa-kiss::before {
+  content: "\f596"; }
+
+.fa-bridge-circle-xmark::before {
+  content: "\e4cb"; }
+
+.fa-face-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-chess-bishop::before {
+  content: "\f43a"; }
+
+.fa-face-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-ear-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deafness::before {
+  content: "\f2a4"; }
+
+.fa-hard-of-hearing::before {
+  content: "\f2a4"; }
+
+.fa-road-circle-check::before {
+  content: "\e564"; }
+
+.fa-dice-five::before {
+  content: "\f523"; }
+
+.fa-square-rss::before {
+  content: "\f143"; }
+
+.fa-rss-square::before {
+  content: "\f143"; }
+
+.fa-land-mine-on::before {
+  content: "\e51b"; }
+
+.fa-i-cursor::before {
+  content: "\f246"; }
+
+.fa-stamp::before {
+  content: "\f5bf"; }
+
+.fa-stairs::before {
+  content: "\e289"; }
+
+.fa-i::before {
+  content: "\49"; }
+
+.fa-hryvnia-sign::before {
+  content: "\f6f2"; }
+
+.fa-hryvnia::before {
+  content: "\f6f2"; }
+
+.fa-pills::before {
+  content: "\f484"; }
+
+.fa-face-grin-wide::before {
+  content: "\f581"; }
+
+.fa-grin-alt::before {
+  content: "\f581"; }
+
+.fa-tooth::before {
+  content: "\f5c9"; }
+
+.fa-v::before {
+  content: "\56"; }
+
+.fa-bangladeshi-taka-sign::before {
+  content: "\e2e6"; }
+
+.fa-bicycle::before {
+  content: "\f206"; }
+
+.fa-staff-snake::before {
+  content: "\e579"; }
+
+.fa-rod-asclepius::before {
+  content: "\e579"; }
+
+.fa-rod-snake::before {
+  content: "\e579"; }
+
+.fa-staff-aesculapius::before {
+  content: "\e579"; }
+
+.fa-head-side-cough-slash::before {
+  content: "\e062"; }
+
+.fa-truck-medical::before {
+  content: "\f0f9"; }
+
+.fa-ambulance::before {
+  content: "\f0f9"; }
+
+.fa-wheat-awn-circle-exclamation::before {
+  content: "\e598"; }
+
+.fa-snowman::before {
+  content: "\f7d0"; }
+
+.fa-mortar-pestle::before {
+  content: "\f5a7"; }
+
+.fa-road-barrier::before {
+  content: "\e562"; }
+
+.fa-school::before {
+  content: "\f549"; }
+
+.fa-igloo::before {
+  content: "\f7ae"; }
+
+.fa-joint::before {
+  content: "\f595"; }
+
+.fa-angle-right::before {
+  content: "\f105"; }
+
+.fa-horse::before {
+  content: "\f6f0"; }
+
+.fa-q::before {
+  content: "\51"; }
+
+.fa-g::before {
+  content: "\47"; }
+
+.fa-notes-medical::before {
+  content: "\f481"; }
+
+.fa-temperature-half::before {
+  content: "\f2c9"; }
+
+.fa-temperature-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-half::before {
+  content: "\f2c9"; }
+
+.fa-dong-sign::before {
+  content: "\e169"; }
+
+.fa-capsules::before {
+  content: "\f46b"; }
+
+.fa-poo-storm::before {
+  content: "\f75a"; }
+
+.fa-poo-bolt::before {
+  content: "\f75a"; }
+
+.fa-face-frown-open::before {
+  content: "\f57a"; }
+
+.fa-frown-open::before {
+  content: "\f57a"; }
+
+.fa-hand-point-up::before {
+  content: "\f0a6"; }
+
+.fa-money-bill::before {
+  content: "\f0d6"; }
+
+.fa-bookmark::before {
+  content: "\f02e"; }
+
+.fa-align-justify::before {
+  content: "\f039"; }
+
+.fa-umbrella-beach::before {
+  content: "\f5ca"; }
+
+.fa-helmet-un::before {
+  content: "\e503"; }
+
+.fa-bullseye::before {
+  content: "\f140"; }
+
+.fa-bacon::before {
+  content: "\f7e5"; }
+
+.fa-hand-point-down::before {
+  content: "\f0a7"; }
+
+.fa-arrow-up-from-bracket::before {
+  content: "\e09a"; }
+
+.fa-folder::before {
+  content: "\f07b"; }
+
+.fa-folder-blank::before {
+  content: "\f07b"; }
+
+.fa-file-waveform::before {
+  content: "\f478"; }
+
+.fa-file-medical-alt::before {
+  content: "\f478"; }
+
+.fa-radiation::before {
+  content: "\f7b9"; }
+
+.fa-chart-simple::before {
+  content: "\e473"; }
+
+.fa-mars-stroke::before {
+  content: "\f229"; }
+
+.fa-vial::before {
+  content: "\f492"; }
+
+.fa-gauge::before {
+  content: "\f624"; }
+
+.fa-dashboard::before {
+  content: "\f624"; }
+
+.fa-gauge-med::before {
+  content: "\f624"; }
+
+.fa-tachometer-alt-average::before {
+  content: "\f624"; }
+
+.fa-wand-magic-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-magic-wand-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-e::before {
+  content: "\45"; }
+
+.fa-pen-clip::before {
+  content: "\f305"; }
+
+.fa-pen-alt::before {
+  content: "\f305"; }
+
+.fa-bridge-circle-exclamation::before {
+  content: "\e4ca"; }
+
+.fa-user::before {
+  content: "\f007"; }
+
+.fa-school-circle-check::before {
+  content: "\e56b"; }
+
+.fa-dumpster::before {
+  content: "\f793"; }
+
+.fa-van-shuttle::before {
+  content: "\f5b6"; }
+
+.fa-shuttle-van::before {
+  content: "\f5b6"; }
+
+.fa-building-user::before {
+  content: "\e4da"; }
+
+.fa-square-caret-left::before {
+  content: "\f191"; }
+
+.fa-caret-square-left::before {
+  content: "\f191"; }
+
+.fa-highlighter::before {
+  content: "\f591"; }
+
+.fa-key::before {
+  content: "\f084"; }
+
+.fa-bullhorn::before {
+  content: "\f0a1"; }
+
+.fa-globe::before {
+  content: "\f0ac"; }
+
+.fa-synagogue::before {
+  content: "\f69b"; }
+
+.fa-person-half-dress::before {
+  content: "\e548"; }
+
+.fa-road-bridge::before {
+  content: "\e563"; }
+
+.fa-location-arrow::before {
+  content: "\f124"; }
+
+.fa-c::before {
+  content: "\43"; }
+
+.fa-tablet-button::before {
+  content: "\f10a"; }
+
+.fa-building-lock::before {
+  content: "\e4d6"; }
+
+.fa-pizza-slice::before {
+  content: "\f818"; }
+
+.fa-money-bill-wave::before {
+  content: "\f53a"; }
+
+.fa-chart-area::before {
+  content: "\f1fe"; }
+
+.fa-area-chart::before {
+  content: "\f1fe"; }
+
+.fa-house-flag::before {
+  content: "\e50d"; }
+
+.fa-person-circle-minus::before {
+  content: "\e540"; }
+
+.fa-ban::before {
+  content: "\f05e"; }
+
+.fa-cancel::before {
+  content: "\f05e"; }
+
+.fa-camera-rotate::before {
+  content: "\e0d8"; }
+
+.fa-spray-can-sparkles::before {
+  content: "\f5d0"; }
+
+.fa-air-freshener::before {
+  content: "\f5d0"; }
+
+.fa-star::before {
+  content: "\f005"; }
+
+.fa-repeat::before {
+  content: "\f363"; }
+
+.fa-cross::before {
+  content: "\f654"; }
+
+.fa-box::before {
+  content: "\f466"; }
+
+.fa-venus-mars::before {
+  content: "\f228"; }
+
+.fa-arrow-pointer::before {
+  content: "\f245"; }
+
+.fa-mouse-pointer::before {
+  content: "\f245"; }
+
+.fa-maximize::before {
+  content: "\f31e"; }
+
+.fa-expand-arrows-alt::before {
+  content: "\f31e"; }
+
+.fa-charging-station::before {
+  content: "\f5e7"; }
+
+.fa-shapes::before {
+  content: "\f61f"; }
+
+.fa-triangle-circle-square::before {
+  content: "\f61f"; }
+
+.fa-shuffle::before {
+  content: "\f074"; }
+
+.fa-random::before {
+  content: "\f074"; }
+
+.fa-person-running::before {
+  content: "\f70c"; }
+
+.fa-running::before {
+  content: "\f70c"; }
+
+.fa-mobile-retro::before {
+  content: "\e527"; }
+
+.fa-grip-lines-vertical::before {
+  content: "\f7a5"; }
+
+.fa-spider::before {
+  content: "\f717"; }
+
+.fa-hands-bound::before {
+  content: "\e4f9"; }
+
+.fa-file-invoice-dollar::before {
+  content: "\f571"; }
+
+.fa-plane-circle-exclamation::before {
+  content: "\e556"; }
+
+.fa-x-ray::before {
+  content: "\f497"; }
+
+.fa-spell-check::before {
+  content: "\f891"; }
+
+.fa-slash::before {
+  content: "\f715"; }
+
+.fa-computer-mouse::before {
+  content: "\f8cc"; }
+
+.fa-mouse::before {
+  content: "\f8cc"; }
+
+.fa-arrow-right-to-bracket::before {
+  content: "\f090"; }
+
+.fa-sign-in::before {
+  content: "\f090"; }
+
+.fa-shop-slash::before {
+  content: "\e070"; }
+
+.fa-store-alt-slash::before {
+  content: "\e070"; }
+
+.fa-server::before {
+  content: "\f233"; }
+
+.fa-virus-covid-slash::before {
+  content: "\e4a9"; }
+
+.fa-shop-lock::before {
+  content: "\e4a5"; }
+
+.fa-hourglass-start::before {
+  content: "\f251"; }
+
+.fa-hourglass-1::before {
+  content: "\f251"; }
+
+.fa-blender-phone::before {
+  content: "\f6b6"; }
+
+.fa-building-wheat::before {
+  content: "\e4db"; }
+
+.fa-person-breastfeeding::before {
+  content: "\e53a"; }
+
+.fa-right-to-bracket::before {
+  content: "\f2f6"; }
+
+.fa-sign-in-alt::before {
+  content: "\f2f6"; }
+
+.fa-venus::before {
+  content: "\f221"; }
+
+.fa-passport::before {
+  content: "\f5ab"; }
+
+.fa-heart-pulse::before {
+  content: "\f21e"; }
+
+.fa-heartbeat::before {
+  content: "\f21e"; }
+
+.fa-people-carry-box::before {
+  content: "\f4ce"; }
+
+.fa-people-carry::before {
+  content: "\f4ce"; }
+
+.fa-temperature-high::before {
+  content: "\f769"; }
+
+.fa-microchip::before {
+  content: "\f2db"; }
+
+.fa-crown::before {
+  content: "\f521"; }
+
+.fa-weight-hanging::before {
+  content: "\f5cd"; }
+
+.fa-xmarks-lines::before {
+  content: "\e59a"; }
+
+.fa-file-prescription::before {
+  content: "\f572"; }
+
+.fa-weight-scale::before {
+  content: "\f496"; }
+
+.fa-weight::before {
+  content: "\f496"; }
+
+.fa-user-group::before {
+  content: "\f500"; }
+
+.fa-user-friends::before {
+  content: "\f500"; }
+
+.fa-arrow-up-a-z::before {
+  content: "\f15e"; }
+
+.fa-sort-alpha-up::before {
+  content: "\f15e"; }
+
+.fa-chess-knight::before {
+  content: "\f441"; }
+
+.fa-face-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-wheelchair::before {
+  content: "\f193"; }
+
+.fa-circle-arrow-up::before {
+  content: "\f0aa"; }
+
+.fa-arrow-circle-up::before {
+  content: "\f0aa"; }
+
+.fa-toggle-on::before {
+  content: "\f205"; }
+
+.fa-person-walking::before {
+  content: "\f554"; }
+
+.fa-walking::before {
+  content: "\f554"; }
+
+.fa-l::before {
+  content: "\4c"; }
+
+.fa-fire::before {
+  content: "\f06d"; }
+
+.fa-bed-pulse::before {
+  content: "\f487"; }
+
+.fa-procedures::before {
+  content: "\f487"; }
+
+.fa-shuttle-space::before {
+  content: "\f197"; }
+
+.fa-space-shuttle::before {
+  content: "\f197"; }
+
+.fa-face-laugh::before {
+  content: "\f599"; }
+
+.fa-laugh::before {
+  content: "\f599"; }
+
+.fa-folder-open::before {
+  content: "\f07c"; }
+
+.fa-heart-circle-plus::before {
+  content: "\e500"; }
+
+.fa-code-fork::before {
+  content: "\e13b"; }
+
+.fa-city::before {
+  content: "\f64f"; }
+
+.fa-microphone-lines::before {
+  content: "\f3c9"; }
+
+.fa-microphone-alt::before {
+  content: "\f3c9"; }
+
+.fa-pepper-hot::before {
+  content: "\f816"; }
+
+.fa-unlock::before {
+  content: "\f09c"; }
+
+.fa-colon-sign::before {
+  content: "\e140"; }
+
+.fa-headset::before {
+  content: "\f590"; }
+
+.fa-store-slash::before {
+  content: "\e071"; }
+
+.fa-road-circle-xmark::before {
+  content: "\e566"; }
+
+.fa-user-minus::before {
+  content: "\f503"; }
+
+.fa-mars-stroke-up::before {
+  content: "\f22a"; }
+
+.fa-mars-stroke-v::before {
+  content: "\f22a"; }
+
+.fa-champagne-glasses::before {
+  content: "\f79f"; }
+
+.fa-glass-cheers::before {
+  content: "\f79f"; }
+
+.fa-clipboard::before {
+  content: "\f328"; }
+
+.fa-house-circle-exclamation::before {
+  content: "\e50a"; }
+
+.fa-file-arrow-up::before {
+  content: "\f574"; }
+
+.fa-file-upload::before {
+  content: "\f574"; }
+
+.fa-wifi::before {
+  content: "\f1eb"; }
+
+.fa-wifi-3::before {
+  content: "\f1eb"; }
+
+.fa-wifi-strong::before {
+  content: "\f1eb"; }
+
+.fa-bath::before {
+  content: "\f2cd"; }
+
+.fa-bathtub::before {
+  content: "\f2cd"; }
+
+.fa-underline::before {
+  content: "\f0cd"; }
+
+.fa-user-pen::before {
+  content: "\f4ff"; }
+
+.fa-user-edit::before {
+  content: "\f4ff"; }
+
+.fa-signature::before {
+  content: "\f5b7"; }
+
+.fa-stroopwafel::before {
+  content: "\f551"; }
+
+.fa-bold::before {
+  content: "\f032"; }
+
+.fa-anchor-lock::before {
+  content: "\e4ad"; }
+
+.fa-building-ngo::before {
+  content: "\e4d7"; }
+
+.fa-manat-sign::before {
+  content: "\e1d5"; }
+
+.fa-not-equal::before {
+  content: "\f53e"; }
+
+.fa-border-top-left::before {
+  content: "\f853"; }
+
+.fa-border-style::before {
+  content: "\f853"; }
+
+.fa-map-location-dot::before {
+  content: "\f5a0"; }
+
+.fa-map-marked-alt::before {
+  content: "\f5a0"; }
+
+.fa-jedi::before {
+  content: "\f669"; }
+
+.fa-square-poll-vertical::before {
+  content: "\f681"; }
+
+.fa-poll::before {
+  content: "\f681"; }
+
+.fa-mug-hot::before {
+  content: "\f7b6"; }
+
+.fa-car-battery::before {
+  content: "\f5df"; }
+
+.fa-battery-car::before {
+  content: "\f5df"; }
+
+.fa-gift::before {
+  content: "\f06b"; }
+
+.fa-dice-two::before {
+  content: "\f528"; }
+
+.fa-chess-queen::before {
+  content: "\f445"; }
+
+.fa-glasses::before {
+  content: "\f530"; }
+
+.fa-chess-board::before {
+  content: "\f43c"; }
+
+.fa-building-circle-check::before {
+  content: "\e4d2"; }
+
+.fa-person-chalkboard::before {
+  content: "\e53d"; }
+
+.fa-mars-stroke-right::before {
+  content: "\f22b"; }
+
+.fa-mars-stroke-h::before {
+  content: "\f22b"; }
+
+.fa-hand-back-fist::before {
+  content: "\f255"; }
+
+.fa-hand-rock::before {
+  content: "\f255"; }
+
+.fa-square-caret-up::before {
+  content: "\f151"; }
+
+.fa-caret-square-up::before {
+  content: "\f151"; }
+
+.fa-cloud-showers-water::before {
+  content: "\e4e4"; }
+
+.fa-chart-bar::before {
+  content: "\f080"; }
+
+.fa-bar-chart::before {
+  content: "\f080"; }
+
+.fa-hands-bubbles::before {
+  content: "\e05e"; }
+
+.fa-hands-wash::before {
+  content: "\e05e"; }
+
+.fa-less-than-equal::before {
+  content: "\f537"; }
+
+.fa-train::before {
+  content: "\f238"; }
+
+.fa-eye-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-crow::before {
+  content: "\f520"; }
+
+.fa-sailboat::before {
+  content: "\e445"; }
+
+.fa-window-restore::before {
+  content: "\f2d2"; }
+
+.fa-square-plus::before {
+  content: "\f0fe"; }
+
+.fa-plus-square::before {
+  content: "\f0fe"; }
+
+.fa-torii-gate::before {
+  content: "\f6a1"; }
+
+.fa-frog::before {
+  content: "\f52e"; }
+
+.fa-bucket::before {
+  content: "\e4cf"; }
+
+.fa-image::before {
+  content: "\f03e"; }
+
+.fa-microphone::before {
+  content: "\f130"; }
+
+.fa-cow::before {
+  content: "\f6c8"; }
+
+.fa-caret-up::before {
+  content: "\f0d8"; }
+
+.fa-screwdriver::before {
+  content: "\f54a"; }
+
+.fa-folder-closed::before {
+  content: "\e185"; }
+
+.fa-house-tsunami::before {
+  content: "\e515"; }
+
+.fa-square-nfi::before {
+  content: "\e576"; }
+
+.fa-arrow-up-from-ground-water::before {
+  content: "\e4b5"; }
+
+.fa-martini-glass::before {
+  content: "\f57b"; }
+
+.fa-glass-martini-alt::before {
+  content: "\f57b"; }
+
+.fa-rotate-left::before {
+  content: "\f2ea"; }
+
+.fa-rotate-back::before {
+  content: "\f2ea"; }
+
+.fa-rotate-backward::before {
+  content: "\f2ea"; }
+
+.fa-undo-alt::before {
+  content: "\f2ea"; }
+
+.fa-table-columns::before {
+  content: "\f0db"; }
+
+.fa-columns::before {
+  content: "\f0db"; }
+
+.fa-lemon::before {
+  content: "\f094"; }
+
+.fa-head-side-mask::before {
+  content: "\e063"; }
+
+.fa-handshake::before {
+  content: "\f2b5"; }
+
+.fa-gem::before {
+  content: "\f3a5"; }
+
+.fa-dolly::before {
+  content: "\f472"; }
+
+.fa-dolly-box::before {
+  content: "\f472"; }
+
+.fa-smoking::before {
+  content: "\f48d"; }
+
+.fa-minimize::before {
+  content: "\f78c"; }
+
+.fa-compress-arrows-alt::before {
+  content: "\f78c"; }
+
+.fa-monument::before {
+  content: "\f5a6"; }
+
+.fa-snowplow::before {
+  content: "\f7d2"; }
+
+.fa-angles-right::before {
+  content: "\f101"; }
+
+.fa-angle-double-right::before {
+  content: "\f101"; }
+
+.fa-cannabis::before {
+  content: "\f55f"; }
+
+.fa-circle-play::before {
+  content: "\f144"; }
+
+.fa-play-circle::before {
+  content: "\f144"; }
+
+.fa-tablets::before {
+  content: "\f490"; }
+
+.fa-ethernet::before {
+  content: "\f796"; }
+
+.fa-euro-sign::before {
+  content: "\f153"; }
+
+.fa-eur::before {
+  content: "\f153"; }
+
+.fa-euro::before {
+  content: "\f153"; }
+
+.fa-chair::before {
+  content: "\f6c0"; }
+
+.fa-circle-check::before {
+  content: "\f058"; }
+
+.fa-check-circle::before {
+  content: "\f058"; }
+
+.fa-circle-stop::before {
+  content: "\f28d"; }
+
+.fa-stop-circle::before {
+  content: "\f28d"; }
+
+.fa-compass-drafting::before {
+  content: "\f568"; }
+
+.fa-drafting-compass::before {
+  content: "\f568"; }
+
+.fa-plate-wheat::before {
+  content: "\e55a"; }
+
+.fa-icicles::before {
+  content: "\f7ad"; }
+
+.fa-person-shelter::before {
+  content: "\e54f"; }
+
+.fa-neuter::before {
+  content: "\f22c"; }
+
+.fa-id-badge::before {
+  content: "\f2c1"; }
+
+.fa-marker::before {
+  content: "\f5a1"; }
+
+.fa-face-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-helicopter-symbol::before {
+  content: "\e502"; }
+
+.fa-universal-access::before {
+  content: "\f29a"; }
+
+.fa-circle-chevron-up::before {
+  content: "\f139"; }
+
+.fa-chevron-circle-up::before {
+  content: "\f139"; }
+
+.fa-lari-sign::before {
+  content: "\e1c8"; }
+
+.fa-volcano::before {
+  content: "\f770"; }
+
+.fa-person-walking-dashed-line-arrow-right::before {
+  content: "\e553"; }
+
+.fa-sterling-sign::before {
+  content: "\f154"; }
+
+.fa-gbp::before {
+  content: "\f154"; }
+
+.fa-pound-sign::before {
+  content: "\f154"; }
+
+.fa-viruses::before {
+  content: "\e076"; }
+
+.fa-square-person-confined::before {
+  content: "\e577"; }
+
+.fa-user-tie::before {
+  content: "\f508"; }
+
+.fa-arrow-down-long::before {
+  content: "\f175"; }
+
+.fa-long-arrow-down::before {
+  content: "\f175"; }
+
+.fa-tent-arrow-down-to-line::before {
+  content: "\e57e"; }
+
+.fa-certificate::before {
+  content: "\f0a3"; }
+
+.fa-reply-all::before {
+  content: "\f122"; }
+
+.fa-mail-reply-all::before {
+  content: "\f122"; }
+
+.fa-suitcase::before {
+  content: "\f0f2"; }
+
+.fa-person-skating::before {
+  content: "\f7c5"; }
+
+.fa-skating::before {
+  content: "\f7c5"; }
+
+.fa-filter-circle-dollar::before {
+  content: "\f662"; }
+
+.fa-funnel-dollar::before {
+  content: "\f662"; }
+
+.fa-camera-retro::before {
+  content: "\f083"; }
+
+.fa-circle-arrow-down::before {
+  content: "\f0ab"; }
+
+.fa-arrow-circle-down::before {
+  content: "\f0ab"; }
+
+.fa-file-import::before {
+  content: "\f56f"; }
+
+.fa-arrow-right-to-file::before {
+  content: "\f56f"; }
+
+.fa-square-arrow-up-right::before {
+  content: "\f14c"; }
+
+.fa-external-link-square::before {
+  content: "\f14c"; }
+
+.fa-box-open::before {
+  content: "\f49e"; }
+
+.fa-scroll::before {
+  content: "\f70e"; }
+
+.fa-spa::before {
+  content: "\f5bb"; }
+
+.fa-location-pin-lock::before {
+  content: "\e51f"; }
+
+.fa-pause::before {
+  content: "\f04c"; }
+
+.fa-hill-avalanche::before {
+  content: "\e507"; }
+
+.fa-temperature-empty::before {
+  content: "\f2cb"; }
+
+.fa-temperature-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-empty::before {
+  content: "\f2cb"; }
+
+.fa-bomb::before {
+  content: "\f1e2"; }
+
+.fa-registered::before {
+  content: "\f25d"; }
+
+.fa-address-card::before {
+  content: "\f2bb"; }
+
+.fa-contact-card::before {
+  content: "\f2bb"; }
+
+.fa-vcard::before {
+  content: "\f2bb"; }
+
+.fa-scale-unbalanced-flip::before {
+  content: "\f516"; }
+
+.fa-balance-scale-right::before {
+  content: "\f516"; }
+
+.fa-subscript::before {
+  content: "\f12c"; }
+
+.fa-diamond-turn-right::before {
+  content: "\f5eb"; }
+
+.fa-directions::before {
+  content: "\f5eb"; }
+
+.fa-burst::before {
+  content: "\e4dc"; }
+
+.fa-house-laptop::before {
+  content: "\e066"; }
+
+.fa-laptop-house::before {
+  content: "\e066"; }
+
+.fa-face-tired::before {
+  content: "\f5c8"; }
+
+.fa-tired::before {
+  content: "\f5c8"; }
+
+.fa-money-bills::before {
+  content: "\e1f3"; }
+
+.fa-smog::before {
+  content: "\f75f"; }
+
+.fa-crutch::before {
+  content: "\f7f7"; }
+
+.fa-cloud-arrow-up::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload-alt::before {
+  content: "\f0ee"; }
+
+.fa-palette::before {
+  content: "\f53f"; }
+
+.fa-arrows-turn-right::before {
+  content: "\e4c0"; }
+
+.fa-vest::before {
+  content: "\e085"; }
+
+.fa-ferry::before {
+  content: "\e4ea"; }
+
+.fa-arrows-down-to-people::before {
+  content: "\e4b9"; }
+
+.fa-seedling::before {
+  content: "\f4d8"; }
+
+.fa-sprout::before {
+  content: "\f4d8"; }
+
+.fa-left-right::before {
+  content: "\f337"; }
+
+.fa-arrows-alt-h::before {
+  content: "\f337"; }
+
+.fa-boxes-packing::before {
+  content: "\e4c7"; }
+
+.fa-circle-arrow-left::before {
+  content: "\f0a8"; }
+
+.fa-arrow-circle-left::before {
+  content: "\f0a8"; }
+
+.fa-group-arrows-rotate::before {
+  content: "\e4f6"; }
+
+.fa-bowl-food::before {
+  content: "\e4c6"; }
+
+.fa-candy-cane::before {
+  content: "\f786"; }
+
+.fa-arrow-down-wide-short::before {
+  content: "\f160"; }
+
+.fa-sort-amount-asc::before {
+  content: "\f160"; }
+
+.fa-sort-amount-down::before {
+  content: "\f160"; }
+
+.fa-cloud-bolt::before {
+  content: "\f76c"; }
+
+.fa-thunderstorm::before {
+  content: "\f76c"; }
+
+.fa-text-slash::before {
+  content: "\f87d"; }
+
+.fa-remove-format::before {
+  content: "\f87d"; }
+
+.fa-face-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-file-word::before {
+  content: "\f1c2"; }
+
+.fa-file-powerpoint::before {
+  content: "\f1c4"; }
+
+.fa-arrows-left-right::before {
+  content: "\f07e"; }
+
+.fa-arrows-h::before {
+  content: "\f07e"; }
+
+.fa-house-lock::before {
+  content: "\e510"; }
+
+.fa-cloud-arrow-down::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download-alt::before {
+  content: "\f0ed"; }
+
+.fa-children::before {
+  content: "\e4e1"; }
+
+.fa-chalkboard::before {
+  content: "\f51b"; }
+
+.fa-blackboard::before {
+  content: "\f51b"; }
+
+.fa-user-large-slash::before {
+  content: "\f4fa"; }
+
+.fa-user-alt-slash::before {
+  content: "\f4fa"; }
+
+.fa-envelope-open::before {
+  content: "\f2b6"; }
+
+.fa-handshake-simple-slash::before {
+  content: "\e05f"; }
+
+.fa-handshake-alt-slash::before {
+  content: "\e05f"; }
+
+.fa-mattress-pillow::before {
+  content: "\e525"; }
+
+.fa-guarani-sign::before {
+  content: "\e19a"; }
+
+.fa-arrows-rotate::before {
+  content: "\f021"; }
+
+.fa-refresh::before {
+  content: "\f021"; }
+
+.fa-sync::before {
+  content: "\f021"; }
+
+.fa-fire-extinguisher::before {
+  content: "\f134"; }
+
+.fa-cruzeiro-sign::before {
+  content: "\e152"; }
+
+.fa-greater-than-equal::before {
+  content: "\f532"; }
+
+.fa-shield-halved::before {
+  content: "\f3ed"; }
+
+.fa-shield-alt::before {
+  content: "\f3ed"; }
+
+.fa-book-atlas::before {
+  content: "\f558"; }
+
+.fa-atlas::before {
+  content: "\f558"; }
+
+.fa-virus::before {
+  content: "\e074"; }
+
+.fa-envelope-circle-check::before {
+  content: "\e4e8"; }
+
+.fa-layer-group::before {
+  content: "\f5fd"; }
+
+.fa-arrows-to-dot::before {
+  content: "\e4be"; }
+
+.fa-archway::before {
+  content: "\f557"; }
+
+.fa-heart-circle-check::before {
+  content: "\e4fd"; }
+
+.fa-house-chimney-crack::before {
+  content: "\f6f1"; }
+
+.fa-house-damage::before {
+  content: "\f6f1"; }
+
+.fa-file-zipper::before {
+  content: "\f1c6"; }
+
+.fa-file-archive::before {
+  content: "\f1c6"; }
+
+.fa-square::before {
+  content: "\f0c8"; }
+
+.fa-martini-glass-empty::before {
+  content: "\f000"; }
+
+.fa-glass-martini::before {
+  content: "\f000"; }
+
+.fa-couch::before {
+  content: "\f4b8"; }
+
+.fa-cedi-sign::before {
+  content: "\e0df"; }
+
+.fa-italic::before {
+  content: "\f033"; }
+
+.fa-church::before {
+  content: "\f51d"; }
+
+.fa-comments-dollar::before {
+  content: "\f653"; }
+
+.fa-democrat::before {
+  content: "\f747"; }
+
+.fa-z::before {
+  content: "\5a"; }
+
+.fa-person-skiing::before {
+  content: "\f7c9"; }
+
+.fa-skiing::before {
+  content: "\f7c9"; }
+
+.fa-road-lock::before {
+  content: "\e567"; }
+
+.fa-a::before {
+  content: "\41"; }
+
+.fa-temperature-arrow-down::before {
+  content: "\e03f"; }
+
+.fa-temperature-down::before {
+  content: "\e03f"; }
+
+.fa-feather-pointed::before {
+  content: "\f56b"; }
+
+.fa-feather-alt::before {
+  content: "\f56b"; }
+
+.fa-p::before {
+  content: "\50"; }
+
+.fa-snowflake::before {
+  content: "\f2dc"; }
+
+.fa-newspaper::before {
+  content: "\f1ea"; }
+
+.fa-rectangle-ad::before {
+  content: "\f641"; }
+
+.fa-ad::before {
+  content: "\f641"; }
+
+.fa-circle-arrow-right::before {
+  content: "\f0a9"; }
+
+.fa-arrow-circle-right::before {
+  content: "\f0a9"; }
+
+.fa-filter-circle-xmark::before {
+  content: "\e17b"; }
+
+.fa-locust::before {
+  content: "\e520"; }
+
+.fa-sort::before {
+  content: "\f0dc"; }
+
+.fa-unsorted::before {
+  content: "\f0dc"; }
+
+.fa-list-ol::before {
+  content: "\f0cb"; }
+
+.fa-list-1-2::before {
+  content: "\f0cb"; }
+
+.fa-list-numeric::before {
+  content: "\f0cb"; }
+
+.fa-person-dress-burst::before {
+  content: "\e544"; }
+
+.fa-money-check-dollar::before {
+  content: "\f53d"; }
+
+.fa-money-check-alt::before {
+  content: "\f53d"; }
+
+.fa-vector-square::before {
+  content: "\f5cb"; }
+
+.fa-bread-slice::before {
+  content: "\f7ec"; }
+
+.fa-language::before {
+  content: "\f1ab"; }
+
+.fa-face-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-filter::before {
+  content: "\f0b0"; }
+
+.fa-question::before {
+  content: "\3f"; }
+
+.fa-file-signature::before {
+  content: "\f573"; }
+
+.fa-up-down-left-right::before {
+  content: "\f0b2"; }
+
+.fa-arrows-alt::before {
+  content: "\f0b2"; }
+
+.fa-house-chimney-user::before {
+  content: "\e065"; }
+
+.fa-hand-holding-heart::before {
+  content: "\f4be"; }
+
+.fa-puzzle-piece::before {
+  content: "\f12e"; }
+
+.fa-money-check::before {
+  content: "\f53c"; }
+
+.fa-star-half-stroke::before {
+  content: "\f5c0"; }
+
+.fa-star-half-alt::before {
+  content: "\f5c0"; }
+
+.fa-code::before {
+  content: "\f121"; }
+
+.fa-whiskey-glass::before {
+  content: "\f7a0"; }
+
+.fa-glass-whiskey::before {
+  content: "\f7a0"; }
+
+.fa-building-circle-exclamation::before {
+  content: "\e4d3"; }
+
+.fa-magnifying-glass-chart::before {
+  content: "\e522"; }
+
+.fa-arrow-up-right-from-square::before {
+  content: "\f08e"; }
+
+.fa-external-link::before {
+  content: "\f08e"; }
+
+.fa-cubes-stacked::before {
+  content: "\e4e6"; }
+
+.fa-won-sign::before {
+  content: "\f159"; }
+
+.fa-krw::before {
+  content: "\f159"; }
+
+.fa-won::before {
+  content: "\f159"; }
+
+.fa-virus-covid::before {
+  content: "\e4a8"; }
+
+.fa-austral-sign::before {
+  content: "\e0a9"; }
+
+.fa-f::before {
+  content: "\46"; }
+
+.fa-leaf::before {
+  content: "\f06c"; }
+
+.fa-road::before {
+  content: "\f018"; }
+
+.fa-taxi::before {
+  content: "\f1ba"; }
+
+.fa-cab::before {
+  content: "\f1ba"; }
+
+.fa-person-circle-plus::before {
+  content: "\e541"; }
+
+.fa-chart-pie::before {
+  content: "\f200"; }
+
+.fa-pie-chart::before {
+  content: "\f200"; }
+
+.fa-bolt-lightning::before {
+  content: "\e0b7"; }
+
+.fa-sack-xmark::before {
+  content: "\e56a"; }
+
+.fa-file-excel::before {
+  content: "\f1c3"; }
+
+.fa-file-contract::before {
+  content: "\f56c"; }
+
+.fa-fish-fins::before {
+  content: "\e4f2"; }
+
+.fa-building-flag::before {
+  content: "\e4d5"; }
+
+.fa-face-grin-beam::before {
+  content: "\f582"; }
+
+.fa-grin-beam::before {
+  content: "\f582"; }
+
+.fa-object-ungroup::before {
+  content: "\f248"; }
+
+.fa-poop::before {
+  content: "\f619"; }
+
+.fa-location-pin::before {
+  content: "\f041"; }
+
+.fa-map-marker::before {
+  content: "\f041"; }
+
+.fa-kaaba::before {
+  content: "\f66b"; }
+
+.fa-toilet-paper::before {
+  content: "\f71e"; }
+
+.fa-helmet-safety::before {
+  content: "\f807"; }
+
+.fa-hard-hat::before {
+  content: "\f807"; }
+
+.fa-hat-hard::before {
+  content: "\f807"; }
+
+.fa-eject::before {
+  content: "\f052"; }
+
+.fa-circle-right::before {
+  content: "\f35a"; }
+
+.fa-arrow-alt-circle-right::before {
+  content: "\f35a"; }
+
+.fa-plane-circle-check::before {
+  content: "\e555"; }
+
+.fa-face-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-meh-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-object-group::before {
+  content: "\f247"; }
+
+.fa-chart-line::before {
+  content: "\f201"; }
+
+.fa-line-chart::before {
+  content: "\f201"; }
+
+.fa-mask-ventilator::before {
+  content: "\e524"; }
+
+.fa-arrow-right::before {
+  content: "\f061"; }
+
+.fa-signs-post::before {
+  content: "\f277"; }
+
+.fa-map-signs::before {
+  content: "\f277"; }
+
+.fa-cash-register::before {
+  content: "\f788"; }
+
+.fa-person-circle-question::before {
+  content: "\e542"; }
+
+.fa-h::before {
+  content: "\48"; }
+
+.fa-tarp::before {
+  content: "\e57b"; }
+
+.fa-screwdriver-wrench::before {
+  content: "\f7d9"; }
+
+.fa-tools::before {
+  content: "\f7d9"; }
+
+.fa-arrows-to-eye::before {
+  content: "\e4bf"; }
+
+.fa-plug-circle-bolt::before {
+  content: "\e55b"; }
+
+.fa-heart::before {
+  content: "\f004"; }
+
+.fa-mars-and-venus::before {
+  content: "\f224"; }
+
+.fa-house-user::before {
+  content: "\e1b0"; }
+
+.fa-home-user::before {
+  content: "\e1b0"; }
+
+.fa-dumpster-fire::before {
+  content: "\f794"; }
+
+.fa-house-crack::before {
+  content: "\e3b1"; }
+
+.fa-martini-glass-citrus::before {
+  content: "\f561"; }
+
+.fa-cocktail::before {
+  content: "\f561"; }
+
+.fa-face-surprise::before {
+  content: "\f5c2"; }
+
+.fa-surprise::before {
+  content: "\f5c2"; }
+
+.fa-bottle-water::before {
+  content: "\e4c5"; }
+
+.fa-circle-pause::before {
+  content: "\f28b"; }
+
+.fa-pause-circle::before {
+  content: "\f28b"; }
+
+.fa-toilet-paper-slash::before {
+  content: "\e072"; }
+
+.fa-apple-whole::before {
+  content: "\f5d1"; }
+
+.fa-apple-alt::before {
+  content: "\f5d1"; }
+
+.fa-kitchen-set::before {
+  content: "\e51a"; }
+
+.fa-r::before {
+  content: "\52"; }
+
+.fa-temperature-quarter::before {
+  content: "\f2ca"; }
+
+.fa-temperature-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-quarter::before {
+  content: "\f2ca"; }
+
+.fa-cube::before {
+  content: "\f1b2"; }
+
+.fa-bitcoin-sign::before {
+  content: "\e0b4"; }
+
+.fa-shield-dog::before {
+  content: "\e573"; }
+
+.fa-solar-panel::before {
+  content: "\f5ba"; }
+
+.fa-lock-open::before {
+  content: "\f3c1"; }
+
+.fa-elevator::before {
+  content: "\e16d"; }
+
+.fa-money-bill-transfer::before {
+  content: "\e528"; }
+
+.fa-money-bill-trend-up::before {
+  content: "\e529"; }
+
+.fa-house-flood-water-circle-arrow-right::before {
+  content: "\e50f"; }
+
+.fa-square-poll-horizontal::before {
+  content: "\f682"; }
+
+.fa-poll-h::before {
+  content: "\f682"; }
+
+.fa-circle::before {
+  content: "\f111"; }
+
+.fa-backward-fast::before {
+  content: "\f049"; }
+
+.fa-fast-backward::before {
+  content: "\f049"; }
+
+.fa-recycle::before {
+  content: "\f1b8"; }
+
+.fa-user-astronaut::before {
+  content: "\f4fb"; }
+
+.fa-plane-slash::before {
+  content: "\e069"; }
+
+.fa-trademark::before {
+  content: "\f25c"; }
+
+.fa-basketball::before {
+  content: "\f434"; }
+
+.fa-basketball-ball::before {
+  content: "\f434"; }
+
+.fa-satellite-dish::before {
+  content: "\f7c0"; }
+
+.fa-circle-up::before {
+  content: "\f35b"; }
+
+.fa-arrow-alt-circle-up::before {
+  content: "\f35b"; }
+
+.fa-mobile-screen-button::before {
+  content: "\f3cd"; }
+
+.fa-mobile-alt::before {
+  content: "\f3cd"; }
+
+.fa-volume-high::before {
+  content: "\f028"; }
+
+.fa-volume-up::before {
+  content: "\f028"; }
+
+.fa-users-rays::before {
+  content: "\e593"; }
+
+.fa-wallet::before {
+  content: "\f555"; }
+
+.fa-clipboard-check::before {
+  content: "\f46c"; }
+
+.fa-file-audio::before {
+  content: "\f1c7"; }
+
+.fa-burger::before {
+  content: "\f805"; }
+
+.fa-hamburger::before {
+  content: "\f805"; }
+
+.fa-wrench::before {
+  content: "\f0ad"; }
+
+.fa-bugs::before {
+  content: "\e4d0"; }
+
+.fa-rupee-sign::before {
+  content: "\f156"; }
+
+.fa-rupee::before {
+  content: "\f156"; }
+
+.fa-file-image::before {
+  content: "\f1c5"; }
+
+.fa-circle-question::before {
+  content: "\f059"; }
+
+.fa-question-circle::before {
+  content: "\f059"; }
+
+.fa-plane-departure::before {
+  content: "\f5b0"; }
+
+.fa-handshake-slash::before {
+  content: "\e060"; }
+
+.fa-book-bookmark::before {
+  content: "\e0bb"; }
+
+.fa-code-branch::before {
+  content: "\f126"; }
+
+.fa-hat-cowboy::before {
+  content: "\f8c0"; }
+
+.fa-bridge::before {
+  content: "\e4c8"; }
+
+.fa-phone-flip::before {
+  content: "\f879"; }
+
+.fa-phone-alt::before {
+  content: "\f879"; }
+
+.fa-truck-front::before {
+  content: "\e2b7"; }
+
+.fa-cat::before {
+  content: "\f6be"; }
+
+.fa-anchor-circle-exclamation::before {
+  content: "\e4ab"; }
+
+.fa-truck-field::before {
+  content: "\e58d"; }
+
+.fa-route::before {
+  content: "\f4d7"; }
+
+.fa-clipboard-question::before {
+  content: "\e4e3"; }
+
+.fa-panorama::before {
+  content: "\e209"; }
+
+.fa-comment-medical::before {
+  content: "\f7f5"; }
+
+.fa-teeth-open::before {
+  content: "\f62f"; }
+
+.fa-file-circle-minus::before {
+  content: "\e4ed"; }
+
+.fa-tags::before {
+  content: "\f02c"; }
+
+.fa-wine-glass::before {
+  content: "\f4e3"; }
+
+.fa-forward-fast::before {
+  content: "\f050"; }
+
+.fa-fast-forward::before {
+  content: "\f050"; }
+
+.fa-face-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-square-parking::before {
+  content: "\f540"; }
+
+.fa-parking::before {
+  content: "\f540"; }
+
+.fa-house-signal::before {
+  content: "\e012"; }
+
+.fa-bars-progress::before {
+  content: "\f828"; }
+
+.fa-tasks-alt::before {
+  content: "\f828"; }
+
+.fa-faucet-drip::before {
+  content: "\e006"; }
+
+.fa-cart-flatbed::before {
+  content: "\f474"; }
+
+.fa-dolly-flatbed::before {
+  content: "\f474"; }
+
+.fa-ban-smoking::before {
+  content: "\f54d"; }
+
+.fa-smoking-ban::before {
+  content: "\f54d"; }
+
+.fa-terminal::before {
+  content: "\f120"; }
+
+.fa-mobile-button::before {
+  content: "\f10b"; }
+
+.fa-house-medical-flag::before {
+  content: "\e514"; }
+
+.fa-basket-shopping::before {
+  content: "\f291"; }
+
+.fa-shopping-basket::before {
+  content: "\f291"; }
+
+.fa-tape::before {
+  content: "\f4db"; }
+
+.fa-bus-simple::before {
+  content: "\f55e"; }
+
+.fa-bus-alt::before {
+  content: "\f55e"; }
+
+.fa-eye::before {
+  content: "\f06e"; }
+
+.fa-face-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-audio-description::before {
+  content: "\f29e"; }
+
+.fa-person-military-to-person::before {
+  content: "\e54c"; }
+
+.fa-file-shield::before {
+  content: "\e4f0"; }
+
+.fa-user-slash::before {
+  content: "\f506"; }
+
+.fa-pen::before {
+  content: "\f304"; }
+
+.fa-tower-observation::before {
+  content: "\e586"; }
+
+.fa-file-code::before {
+  content: "\f1c9"; }
+
+.fa-signal::before {
+  content: "\f012"; }
+
+.fa-signal-5::before {
+  content: "\f012"; }
+
+.fa-signal-perfect::before {
+  content: "\f012"; }
+
+.fa-bus::before {
+  content: "\f207"; }
+
+.fa-heart-circle-xmark::before {
+  content: "\e501"; }
+
+.fa-house-chimney::before {
+  content: "\e3af"; }
+
+.fa-home-lg::before {
+  content: "\e3af"; }
+
+.fa-window-maximize::before {
+  content: "\f2d0"; }
+
+.fa-face-frown::before {
+  content: "\f119"; }
+
+.fa-frown::before {
+  content: "\f119"; }
+
+.fa-prescription::before {
+  content: "\f5b1"; }
+
+.fa-shop::before {
+  content: "\f54f"; }
+
+.fa-store-alt::before {
+  content: "\f54f"; }
+
+.fa-floppy-disk::before {
+  content: "\f0c7"; }
+
+.fa-save::before {
+  content: "\f0c7"; }
+
+.fa-vihara::before {
+  content: "\f6a7"; }
+
+.fa-scale-unbalanced::before {
+  content: "\f515"; }
+
+.fa-balance-scale-left::before {
+  content: "\f515"; }
+
+.fa-sort-up::before {
+  content: "\f0de"; }
+
+.fa-sort-asc::before {
+  content: "\f0de"; }
+
+.fa-comment-dots::before {
+  content: "\f4ad"; }
+
+.fa-commenting::before {
+  content: "\f4ad"; }
+
+.fa-plant-wilt::before {
+  content: "\e5aa"; }
+
+.fa-diamond::before {
+  content: "\f219"; }
+
+.fa-face-grin-squint::before {
+  content: "\f585"; }
+
+.fa-grin-squint::before {
+  content: "\f585"; }
+
+.fa-hand-holding-dollar::before {
+  content: "\f4c0"; }
+
+.fa-hand-holding-usd::before {
+  content: "\f4c0"; }
+
+.fa-bacterium::before {
+  content: "\e05a"; }
+
+.fa-hand-pointer::before {
+  content: "\f25a"; }
+
+.fa-drum-steelpan::before {
+  content: "\f56a"; }
+
+.fa-hand-scissors::before {
+  content: "\f257"; }
+
+.fa-hands-praying::before {
+  content: "\f684"; }
+
+.fa-praying-hands::before {
+  content: "\f684"; }
+
+.fa-arrow-rotate-right::before {
+  content: "\f01e"; }
+
+.fa-arrow-right-rotate::before {
+  content: "\f01e"; }
+
+.fa-arrow-rotate-forward::before {
+  content: "\f01e"; }
+
+.fa-redo::before {
+  content: "\f01e"; }
+
+.fa-biohazard::before {
+  content: "\f780"; }
+
+.fa-location-crosshairs::before {
+  content: "\f601"; }
+
+.fa-location::before {
+  content: "\f601"; }
+
+.fa-mars-double::before {
+  content: "\f227"; }
+
+.fa-child-dress::before {
+  content: "\e59c"; }
+
+.fa-users-between-lines::before {
+  content: "\e591"; }
+
+.fa-lungs-virus::before {
+  content: "\e067"; }
+
+.fa-face-grin-tears::before {
+  content: "\f588"; }
+
+.fa-grin-tears::before {
+  content: "\f588"; }
+
+.fa-phone::before {
+  content: "\f095"; }
+
+.fa-calendar-xmark::before {
+  content: "\f273"; }
+
+.fa-calendar-times::before {
+  content: "\f273"; }
+
+.fa-child-reaching::before {
+  content: "\e59d"; }
+
+.fa-head-side-virus::before {
+  content: "\e064"; }
+
+.fa-user-gear::before {
+  content: "\f4fe"; }
+
+.fa-user-cog::before {
+  content: "\f4fe"; }
+
+.fa-arrow-up-1-9::before {
+  content: "\f163"; }
+
+.fa-sort-numeric-up::before {
+  content: "\f163"; }
+
+.fa-door-closed::before {
+  content: "\f52a"; }
+
+.fa-shield-virus::before {
+  content: "\e06c"; }
+
+.fa-dice-six::before {
+  content: "\f526"; }
+
+.fa-mosquito-net::before {
+  content: "\e52c"; }
+
+.fa-bridge-water::before {
+  content: "\e4ce"; }
+
+.fa-person-booth::before {
+  content: "\f756"; }
+
+.fa-text-width::before {
+  content: "\f035"; }
+
+.fa-hat-wizard::before {
+  content: "\f6e8"; }
+
+.fa-pen-fancy::before {
+  content: "\f5ac"; }
+
+.fa-person-digging::before {
+  content: "\f85e"; }
+
+.fa-digging::before {
+  content: "\f85e"; }
+
+.fa-trash::before {
+  content: "\f1f8"; }
+
+.fa-gauge-simple::before {
+  content: "\f629"; }
+
+.fa-gauge-simple-med::before {
+  content: "\f629"; }
+
+.fa-tachometer-average::before {
+  content: "\f629"; }
+
+.fa-book-medical::before {
+  content: "\f7e6"; }
+
+.fa-poo::before {
+  content: "\f2fe"; }
+
+.fa-quote-right::before {
+  content: "\f10e"; }
+
+.fa-quote-right-alt::before {
+  content: "\f10e"; }
+
+.fa-shirt::before {
+  content: "\f553"; }
+
+.fa-t-shirt::before {
+  content: "\f553"; }
+
+.fa-tshirt::before {
+  content: "\f553"; }
+
+.fa-cubes::before {
+  content: "\f1b3"; }
+
+.fa-divide::before {
+  content: "\f529"; }
+
+.fa-tenge-sign::before {
+  content: "\f7d7"; }
+
+.fa-tenge::before {
+  content: "\f7d7"; }
+
+.fa-headphones::before {
+  content: "\f025"; }
+
+.fa-hands-holding::before {
+  content: "\f4c2"; }
+
+.fa-hands-clapping::before {
+  content: "\e1a8"; }
+
+.fa-republican::before {
+  content: "\f75e"; }
+
+.fa-arrow-left::before {
+  content: "\f060"; }
+
+.fa-person-circle-xmark::before {
+  content: "\e543"; }
+
+.fa-ruler::before {
+  content: "\f545"; }
+
+.fa-align-left::before {
+  content: "\f036"; }
+
+.fa-dice-d6::before {
+  content: "\f6d1"; }
+
+.fa-restroom::before {
+  content: "\f7bd"; }
+
+.fa-j::before {
+  content: "\4a"; }
+
+.fa-users-viewfinder::before {
+  content: "\e595"; }
+
+.fa-file-video::before {
+  content: "\f1c8"; }
+
+.fa-up-right-from-square::before {
+  content: "\f35d"; }
+
+.fa-external-link-alt::before {
+  content: "\f35d"; }
+
+.fa-table-cells::before {
+  content: "\f00a"; }
+
+.fa-th::before {
+  content: "\f00a"; }
+
+.fa-file-pdf::before {
+  content: "\f1c1"; }
+
+.fa-book-bible::before {
+  content: "\f647"; }
+
+.fa-bible::before {
+  content: "\f647"; }
+
+.fa-o::before {
+  content: "\4f"; }
+
+.fa-suitcase-medical::before {
+  content: "\f0fa"; }
+
+.fa-medkit::before {
+  content: "\f0fa"; }
+
+.fa-user-secret::before {
+  content: "\f21b"; }
+
+.fa-otter::before {
+  content: "\f700"; }
+
+.fa-person-dress::before {
+  content: "\f182"; }
+
+.fa-female::before {
+  content: "\f182"; }
+
+.fa-comment-dollar::before {
+  content: "\f651"; }
+
+.fa-business-time::before {
+  content: "\f64a"; }
+
+.fa-briefcase-clock::before {
+  content: "\f64a"; }
+
+.fa-table-cells-large::before {
+  content: "\f009"; }
+
+.fa-th-large::before {
+  content: "\f009"; }
+
+.fa-book-tanakh::before {
+  content: "\f827"; }
+
+.fa-tanakh::before {
+  content: "\f827"; }
+
+.fa-phone-volume::before {
+  content: "\f2a0"; }
+
+.fa-volume-control-phone::before {
+  content: "\f2a0"; }
+
+.fa-hat-cowboy-side::before {
+  content: "\f8c1"; }
+
+.fa-clipboard-user::before {
+  content: "\f7f3"; }
+
+.fa-child::before {
+  content: "\f1ae"; }
+
+.fa-lira-sign::before {
+  content: "\f195"; }
+
+.fa-satellite::before {
+  content: "\f7bf"; }
+
+.fa-plane-lock::before {
+  content: "\e558"; }
+
+.fa-tag::before {
+  content: "\f02b"; }
+
+.fa-comment::before {
+  content: "\f075"; }
+
+.fa-cake-candles::before {
+  content: "\f1fd"; }
+
+.fa-birthday-cake::before {
+  content: "\f1fd"; }
+
+.fa-cake::before {
+  content: "\f1fd"; }
+
+.fa-envelope::before {
+  content: "\f0e0"; }
+
+.fa-angles-up::before {
+  content: "\f102"; }
+
+.fa-angle-double-up::before {
+  content: "\f102"; }
+
+.fa-paperclip::before {
+  content: "\f0c6"; }
+
+.fa-arrow-right-to-city::before {
+  content: "\e4b3"; }
+
+.fa-ribbon::before {
+  content: "\f4d6"; }
+
+.fa-lungs::before {
+  content: "\f604"; }
+
+.fa-arrow-up-9-1::before {
+  content: "\f887"; }
+
+.fa-sort-numeric-up-alt::before {
+  content: "\f887"; }
+
+.fa-litecoin-sign::before {
+  content: "\e1d3"; }
+
+.fa-border-none::before {
+  content: "\f850"; }
+
+.fa-circle-nodes::before {
+  content: "\e4e2"; }
+
+.fa-parachute-box::before {
+  content: "\f4cd"; }
+
+.fa-indent::before {
+  content: "\f03c"; }
+
+.fa-truck-field-un::before {
+  content: "\e58e"; }
+
+.fa-hourglass::before {
+  content: "\f254"; }
+
+.fa-hourglass-empty::before {
+  content: "\f254"; }
+
+.fa-mountain::before {
+  content: "\f6fc"; }
+
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+  content: "\f0f0"; }
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+  content: "\f0f0"; }
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+  content: "\f05a"; }
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+  content: "\f05a"; }
+
+.fa-cloud-meatball::before {
+  content: "\f73b"; }
+
+.fa-camera::before {
+  content: "\f030"; }
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+.fa-camera-alt::before {
+  content: "\f030"; }
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+.fa-square-virus::before {
+  content: "\e578"; }
+
+.fa-meteor::before {
+  content: "\f753"; }
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+.fa-car-on::before {
+  content: "\e4dd"; }
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+.fa-sleigh::before {
+  content: "\f7cc"; }
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+  content: "\f162"; }
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+  content: "\f162"; }
+
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+  content: "\f162"; }
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+  content: "\f4c1"; }
+
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+  content: "\f4c1"; }
+
+.fa-water::before {
+  content: "\f773"; }
+
+.fa-calendar-check::before {
+  content: "\f274"; }
+
+.fa-braille::before {
+  content: "\f2a1"; }
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+.fa-prescription-bottle-medical::before {
+  content: "\f486"; }
+
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+  content: "\f486"; }
+
+.fa-landmark::before {
+  content: "\f66f"; }
+
+.fa-truck::before {
+  content: "\f0d1"; }
+
+.fa-crosshairs::before {
+  content: "\f05b"; }
+
+.fa-person-cane::before {
+  content: "\e53c"; }
+
+.fa-tent::before {
+  content: "\e57d"; }
+
+.fa-vest-patches::before {
+  content: "\e086"; }
+
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+  content: "\f560"; }
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+  content: "\f15d"; }
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+  content: "\f15d"; }
+
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+  content: "\f15d"; }
+
+.fa-money-bill-wheat::before {
+  content: "\e52a"; }
+
+.fa-cookie::before {
+  content: "\f563"; }
+
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+  content: "\f0e2"; }
+
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+  content: "\f0e2"; }
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+  content: "\f0e2"; }
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+  content: "\f0e2"; }
+
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+  content: "\f0e2"; }
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+  content: "\f0a0"; }
+
+.fa-hdd::before {
+  content: "\f0a0"; }
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+.fa-face-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-dumbbell::before {
+  content: "\f44b"; }
+
+.fa-rectangle-list::before {
+  content: "\f022"; }
+
+.fa-list-alt::before {
+  content: "\f022"; }
+
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+  content: "\e57c"; }
+
+.fa-house-medical-circle-check::before {
+  content: "\e511"; }
+
+.fa-person-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-calendar-plus::before {
+  content: "\f271"; }
+
+.fa-plane-arrival::before {
+  content: "\f5af"; }
+
+.fa-circle-left::before {
+  content: "\f359"; }
+
+.fa-arrow-alt-circle-left::before {
+  content: "\f359"; }
+
+.fa-train-subway::before {
+  content: "\f239"; }
+
+.fa-subway::before {
+  content: "\f239"; }
+
+.fa-chart-gantt::before {
+  content: "\e0e4"; }
+
+.fa-indian-rupee-sign::before {
+  content: "\e1bc"; }
+
+.fa-indian-rupee::before {
+  content: "\e1bc"; }
+
+.fa-inr::before {
+  content: "\e1bc"; }
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+.fa-crop-simple::before {
+  content: "\f565"; }
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+.fa-crop-alt::before {
+  content: "\f565"; }
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+.fa-money-bill-1::before {
+  content: "\f3d1"; }
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+  content: "\f3d1"; }
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+.fa-left-long::before {
+  content: "\f30a"; }
+
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+  content: "\f30a"; }
+
+.fa-dna::before {
+  content: "\f471"; }
+
+.fa-virus-slash::before {
+  content: "\e075"; }
+
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+  content: "\f068"; }
+
+.fa-subtract::before {
+  content: "\f068"; }
+
+.fa-chess::before {
+  content: "\f439"; }
+
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+  content: "\f177"; }
+
+.fa-long-arrow-left::before {
+  content: "\f177"; }
+
+.fa-plug-circle-check::before {
+  content: "\e55c"; }
+
+.fa-street-view::before {
+  content: "\f21d"; }
+
+.fa-franc-sign::before {
+  content: "\e18f"; }
+
+.fa-volume-off::before {
+  content: "\f026"; }
+
+.fa-hands-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-hands-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-gear::before {
+  content: "\f013"; }
+
+.fa-cog::before {
+  content: "\f013"; }
+
+.fa-droplet-slash::before {
+  content: "\f5c7"; }
+
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+  content: "\f5c7"; }
+
+.fa-mosque::before {
+  content: "\f678"; }
+
+.fa-mosquito::before {
+  content: "\e52b"; }
+
+.fa-star-of-david::before {
+  content: "\f69a"; }
+
+.fa-person-military-rifle::before {
+  content: "\e54b"; }
+
+.fa-cart-shopping::before {
+  content: "\f07a"; }
+
+.fa-shopping-cart::before {
+  content: "\f07a"; }
+
+.fa-vials::before {
+  content: "\f493"; }
+
+.fa-plug-circle-plus::before {
+  content: "\e55f"; }
+
+.fa-place-of-worship::before {
+  content: "\f67f"; }
+
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+  content: "\f58e"; }
+
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+  content: "\f148"; }
+
+.fa-level-up::before {
+  content: "\f148"; }
+
+.fa-u::before {
+  content: "\55"; }
+
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+  content: "\f698"; }
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+.fa-square-root-alt::before {
+  content: "\f698"; }
+
+.fa-clock::before {
+  content: "\f017"; }
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+.fa-clock-four::before {
+  content: "\f017"; }
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+.fa-backward-step::before {
+  content: "\f048"; }
+
+.fa-step-backward::before {
+  content: "\f048"; }
+
+.fa-pallet::before {
+  content: "\f482"; }
+
+.fa-faucet::before {
+  content: "\e005"; }
+
+.fa-baseball-bat-ball::before {
+  content: "\f432"; }
+
+.fa-s::before {
+  content: "\53"; }
+
+.fa-timeline::before {
+  content: "\e29c"; }
+
+.fa-keyboard::before {
+  content: "\f11c"; }
+
+.fa-caret-down::before {
+  content: "\f0d7"; }
+
+.fa-house-chimney-medical::before {
+  content: "\f7f2"; }
+
+.fa-clinic-medical::before {
+  content: "\f7f2"; }
+
+.fa-temperature-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-temperature-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-mobile-screen::before {
+  content: "\f3cf"; }
+
+.fa-mobile-android-alt::before {
+  content: "\f3cf"; }
+
+.fa-plane-up::before {
+  content: "\e22d"; }
+
+.fa-piggy-bank::before {
+  content: "\f4d3"; }
+
+.fa-battery-half::before {
+  content: "\f242"; }
+
+.fa-battery-3::before {
+  content: "\f242"; }
+
+.fa-mountain-city::before {
+  content: "\e52e"; }
+
+.fa-coins::before {
+  content: "\f51e"; }
+
+.fa-khanda::before {
+  content: "\f66d"; }
+
+.fa-sliders::before {
+  content: "\f1de"; }
+
+.fa-sliders-h::before {
+  content: "\f1de"; }
+
+.fa-folder-tree::before {
+  content: "\f802"; }
+
+.fa-network-wired::before {
+  content: "\f6ff"; }
+
+.fa-map-pin::before {
+  content: "\f276"; }
+
+.fa-hamsa::before {
+  content: "\f665"; }
+
+.fa-cent-sign::before {
+  content: "\e3f5"; }
+
+.fa-flask::before {
+  content: "\f0c3"; }
+
+.fa-person-pregnant::before {
+  content: "\e31e"; }
+
+.fa-wand-sparkles::before {
+  content: "\f72b"; }
+
+.fa-ellipsis-vertical::before {
+  content: "\f142"; }
+
+.fa-ellipsis-v::before {
+  content: "\f142"; }
+
+.fa-ticket::before {
+  content: "\f145"; }
+
+.fa-power-off::before {
+  content: "\f011"; }
+
+.fa-right-long::before {
+  content: "\f30b"; }
+
+.fa-long-arrow-alt-right::before {
+  content: "\f30b"; }
+
+.fa-flag-usa::before {
+  content: "\f74d"; }
+
+.fa-laptop-file::before {
+  content: "\e51d"; }
+
+.fa-tty::before {
+  content: "\f1e4"; }
+
+.fa-teletype::before {
+  content: "\f1e4"; }
+
+.fa-diagram-next::before {
+  content: "\e476"; }
+
+.fa-person-rifle::before {
+  content: "\e54e"; }
+
+.fa-house-medical-circle-exclamation::before {
+  content: "\e512"; }
+
+.fa-closed-captioning::before {
+  content: "\f20a"; }
+
+.fa-person-hiking::before {
+  content: "\f6ec"; }
+
+.fa-hiking::before {
+  content: "\f6ec"; }
+
+.fa-venus-double::before {
+  content: "\f226"; }
+
+.fa-images::before {
+  content: "\f302"; }
+
+.fa-calculator::before {
+  content: "\f1ec"; }
+
+.fa-people-pulling::before {
+  content: "\e535"; }
+
+.fa-n::before {
+  content: "\4e"; }
+
+.fa-cable-car::before {
+  content: "\f7da"; }
+
+.fa-tram::before {
+  content: "\f7da"; }
+
+.fa-cloud-rain::before {
+  content: "\f73d"; }
+
+.fa-building-circle-xmark::before {
+  content: "\e4d4"; }
+
+.fa-ship::before {
+  content: "\f21a"; }
+
+.fa-arrows-down-to-line::before {
+  content: "\e4b8"; }
+
+.fa-download::before {
+  content: "\f019"; }
+
+.fa-face-grin::before {
+  content: "\f580"; }
+
+.fa-grin::before {
+  content: "\f580"; }
+
+.fa-delete-left::before {
+  content: "\f55a"; }
+
+.fa-backspace::before {
+  content: "\f55a"; }
+
+.fa-eye-dropper::before {
+  content: "\f1fb"; }
+
+.fa-eye-dropper-empty::before {
+  content: "\f1fb"; }
+
+.fa-eyedropper::before {
+  content: "\f1fb"; }
+
+.fa-file-circle-check::before {
+  content: "\e5a0"; }
+
+.fa-forward::before {
+  content: "\f04e"; }
+
+.fa-mobile::before {
+  content: "\f3ce"; }
+
+.fa-mobile-android::before {
+  content: "\f3ce"; }
+
+.fa-mobile-phone::before {
+  content: "\f3ce"; }
+
+.fa-face-meh::before {
+  content: "\f11a"; }
+
+.fa-meh::before {
+  content: "\f11a"; }
+
+.fa-align-center::before {
+  content: "\f037"; }
+
+.fa-book-skull::before {
+  content: "\f6b7"; }
+
+.fa-book-dead::before {
+  content: "\f6b7"; }
+
+.fa-id-card::before {
+  content: "\f2c2"; }
+
+.fa-drivers-license::before {
+  content: "\f2c2"; }
+
+.fa-outdent::before {
+  content: "\f03b"; }
+
+.fa-dedent::before {
+  content: "\f03b"; }
+
+.fa-heart-circle-exclamation::before {
+  content: "\e4fe"; }
+
+.fa-house::before {
+  content: "\f015"; }
+
+.fa-home::before {
+  content: "\f015"; }
+
+.fa-home-alt::before {
+  content: "\f015"; }
+
+.fa-home-lg-alt::before {
+  content: "\f015"; }
+
+.fa-calendar-week::before {
+  content: "\f784"; }
+
+.fa-laptop-medical::before {
+  content: "\f812"; }
+
+.fa-b::before {
+  content: "\42"; }
+
+.fa-file-medical::before {
+  content: "\f477"; }
+
+.fa-dice-one::before {
+  content: "\f525"; }
+
+.fa-kiwi-bird::before {
+  content: "\f535"; }
+
+.fa-arrow-right-arrow-left::before {
+  content: "\f0ec"; }
+
+.fa-exchange::before {
+  content: "\f0ec"; }
+
+.fa-rotate-right::before {
+  content: "\f2f9"; }
+
+.fa-redo-alt::before {
+  content: "\f2f9"; }
+
+.fa-rotate-forward::before {
+  content: "\f2f9"; }
+
+.fa-utensils::before {
+  content: "\f2e7"; }
+
+.fa-cutlery::before {
+  content: "\f2e7"; }
+
+.fa-arrow-up-wide-short::before {
+  content: "\f161"; }
+
+.fa-sort-amount-up::before {
+  content: "\f161"; }
+
+.fa-mill-sign::before {
+  content: "\e1ed"; }
+
+.fa-bowl-rice::before {
+  content: "\e2eb"; }
+
+.fa-skull::before {
+  content: "\f54c"; }
+
+.fa-tower-broadcast::before {
+  content: "\f519"; }
+
+.fa-broadcast-tower::before {
+  content: "\f519"; }
+
+.fa-truck-pickup::before {
+  content: "\f63c"; }
+
+.fa-up-long::before {
+  content: "\f30c"; }
+
+.fa-long-arrow-alt-up::before {
+  content: "\f30c"; }
+
+.fa-stop::before {
+  content: "\f04d"; }
+
+.fa-code-merge::before {
+  content: "\f387"; }
+
+.fa-upload::before {
+  content: "\f093"; }
+
+.fa-hurricane::before {
+  content: "\f751"; }
+
+.fa-mound::before {
+  content: "\e52d"; }
+
+.fa-toilet-portable::before {
+  content: "\e583"; }
+
+.fa-compact-disc::before {
+  content: "\f51f"; }
+
+.fa-file-arrow-down::before {
+  content: "\f56d"; }
+
+.fa-file-download::before {
+  content: "\f56d"; }
+
+.fa-caravan::before {
+  content: "\f8ff"; }
+
+.fa-shield-cat::before {
+  content: "\e572"; }
+
+.fa-bolt::before {
+  content: "\f0e7"; }
+
+.fa-zap::before {
+  content: "\f0e7"; }
+
+.fa-glass-water::before {
+  content: "\e4f4"; }
+
+.fa-oil-well::before {
+  content: "\e532"; }
+
+.fa-vault::before {
+  content: "\e2c5"; }
+
+.fa-mars::before {
+  content: "\f222"; }
+
+.fa-toilet::before {
+  content: "\f7d8"; }
+
+.fa-plane-circle-xmark::before {
+  content: "\e557"; }
+
+.fa-yen-sign::before {
+  content: "\f157"; }
+
+.fa-cny::before {
+  content: "\f157"; }
+
+.fa-jpy::before {
+  content: "\f157"; }
+
+.fa-rmb::before {
+  content: "\f157"; }
+
+.fa-yen::before {
+  content: "\f157"; }
+
+.fa-ruble-sign::before {
+  content: "\f158"; }
+
+.fa-rouble::before {
+  content: "\f158"; }
+
+.fa-rub::before {
+  content: "\f158"; }
+
+.fa-ruble::before {
+  content: "\f158"; }
+
+.fa-sun::before {
+  content: "\f185"; }
+
+.fa-guitar::before {
+  content: "\f7a6"; }
+
+.fa-face-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-horse-head::before {
+  content: "\f7ab"; }
+
+.fa-bore-hole::before {
+  content: "\e4c3"; }
+
+.fa-industry::before {
+  content: "\f275"; }
+
+.fa-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrow-alt-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrows-turn-to-dots::before {
+  content: "\e4c1"; }
+
+.fa-florin-sign::before {
+  content: "\e184"; }
+
+.fa-arrow-down-short-wide::before {
+  content: "\f884"; }
+
+.fa-sort-amount-desc::before {
+  content: "\f884"; }
+
+.fa-sort-amount-down-alt::before {
+  content: "\f884"; }
+
+.fa-less-than::before {
+  content: "\3c"; }
+
+.fa-angle-down::before {
+  content: "\f107"; }
+
+.fa-car-tunnel::before {
+  content: "\e4de"; }
+
+.fa-head-side-cough::before {
+  content: "\e061"; }
+
+.fa-grip-lines::before {
+  content: "\f7a4"; }
+
+.fa-thumbs-down::before {
+  content: "\f165"; }
+
+.fa-user-lock::before {
+  content: "\f502"; }
+
+.fa-arrow-right-long::before {
+  content: "\f178"; }
+
+.fa-long-arrow-right::before {
+  content: "\f178"; }
+
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+  content: "\e4ac"; }
+
+.fa-ellipsis::before {
+  content: "\f141"; }
+
+.fa-ellipsis-h::before {
+  content: "\f141"; }
+
+.fa-chess-pawn::before {
+  content: "\f443"; }
+
+.fa-kit-medical::before {
+  content: "\f479"; }
+
+.fa-first-aid::before {
+  content: "\f479"; }
+
+.fa-person-through-window::before {
+  content: "\e5a9"; }
+
+.fa-toolbox::before {
+  content: "\f552"; }
+
+.fa-hands-holding-circle::before {
+  content: "\e4fb"; }
+
+.fa-bug::before {
+  content: "\f188"; }
+
+.fa-credit-card::before {
+  content: "\f09d"; }
+
+.fa-credit-card-alt::before {
+  content: "\f09d"; }
+
+.fa-car::before {
+  content: "\f1b9"; }
+
+.fa-automobile::before {
+  content: "\f1b9"; }
+
+.fa-hand-holding-hand::before {
+  content: "\e4f7"; }
+
+.fa-book-open-reader::before {
+  content: "\f5da"; }
+
+.fa-book-reader::before {
+  content: "\f5da"; }
+
+.fa-mountain-sun::before {
+  content: "\e52f"; }
+
+.fa-arrows-left-right-to-line::before {
+  content: "\e4ba"; }
+
+.fa-dice-d20::before {
+  content: "\f6cf"; }
+
+.fa-truck-droplet::before {
+  content: "\e58c"; }
+
+.fa-file-circle-xmark::before {
+  content: "\e5a1"; }
+
+.fa-temperature-arrow-up::before {
+  content: "\e040"; }
+
+.fa-temperature-up::before {
+  content: "\e040"; }
+
+.fa-medal::before {
+  content: "\f5a2"; }
+
+.fa-bed::before {
+  content: "\f236"; }
+
+.fa-square-h::before {
+  content: "\f0fd"; }
+
+.fa-h-square::before {
+  content: "\f0fd"; }
+
+.fa-podcast::before {
+  content: "\f2ce"; }
+
+.fa-temperature-full::before {
+  content: "\f2c7"; }
+
+.fa-temperature-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-full::before {
+  content: "\f2c7"; }
+
+.fa-bell::before {
+  content: "\f0f3"; }
+
+.fa-superscript::before {
+  content: "\f12b"; }
+
+.fa-plug-circle-xmark::before {
+  content: "\e560"; }
+
+.fa-star-of-life::before {
+  content: "\f621"; }
+
+.fa-phone-slash::before {
+  content: "\f3dd"; }
+
+.fa-paint-roller::before {
+  content: "\f5aa"; }
+
+.fa-handshake-angle::before {
+  content: "\f4c4"; }
+
+.fa-hands-helping::before {
+  content: "\f4c4"; }
+
+.fa-location-dot::before {
+  content: "\f3c5"; }
+
+.fa-map-marker-alt::before {
+  content: "\f3c5"; }
+
+.fa-file::before {
+  content: "\f15b"; }
+
+.fa-greater-than::before {
+  content: "\3e"; }
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+  content: "\f5c4"; }
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+.fa-swimmer::before {
+  content: "\f5c4"; }
+
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+  content: "\f063"; }
+
+.fa-droplet::before {
+  content: "\f043"; }
+
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+  content: "\f043"; }
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+  content: "\f12d"; }
+
+.fa-earth-americas::before {
+  content: "\f57d"; }
+
+.fa-earth::before {
+  content: "\f57d"; }
+
+.fa-earth-america::before {
+  content: "\f57d"; }
+
+.fa-globe-americas::before {
+  content: "\f57d"; }
+
+.fa-person-burst::before {
+  content: "\e53b"; }
+
+.fa-dove::before {
+  content: "\f4ba"; }
+
+.fa-battery-empty::before {
+  content: "\f244"; }
+
+.fa-battery-0::before {
+  content: "\f244"; }
+
+.fa-socks::before {
+  content: "\f696"; }
+
+.fa-inbox::before {
+  content: "\f01c"; }
+
+.fa-section::before {
+  content: "\e447"; }
+
+.fa-gauge-high::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt-fast::before {
+  content: "\f625"; }
+
+.fa-envelope-open-text::before {
+  content: "\f658"; }
+
+.fa-hospital::before {
+  content: "\f0f8"; }
+
+.fa-hospital-alt::before {
+  content: "\f0f8"; }
+
+.fa-hospital-wide::before {
+  content: "\f0f8"; }
+
+.fa-wine-bottle::before {
+  content: "\f72f"; }
+
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+  content: "\f447"; }
+
+.fa-bars-staggered::before {
+  content: "\f550"; }
+
+.fa-reorder::before {
+  content: "\f550"; }
+
+.fa-stream::before {
+  content: "\f550"; }
+
+.fa-dharmachakra::before {
+  content: "\f655"; }
+
+.fa-hotdog::before {
+  content: "\f80f"; }
+
+.fa-person-walking-with-cane::before {
+  content: "\f29d"; }
+
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+  content: "\f29d"; }
+
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+  content: "\f569"; }
+
+.fa-ice-cream::before {
+  content: "\f810"; }
+
+.fa-heart-circle-bolt::before {
+  content: "\e4fc"; }
+
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+  content: "\f1ac"; }
+
+.fa-paragraph::before {
+  content: "\f1dd"; }
+
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+  content: "\f772"; }
+
+.fa-vote-yea::before {
+  content: "\f772"; }
+
+.fa-star-half::before {
+  content: "\f089"; }
+
+.fa-boxes-stacked::before {
+  content: "\f468"; }
+
+.fa-boxes::before {
+  content: "\f468"; }
+
+.fa-boxes-alt::before {
+  content: "\f468"; }
+
+.fa-link::before {
+  content: "\f0c1"; }
+
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+  content: "\f0c1"; }
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+  content: "\f2a2"; }
+
+.fa-assistive-listening-systems::before {
+  content: "\f2a2"; }
+
+.fa-tree-city::before {
+  content: "\e587"; }
+
+.fa-play::before {
+  content: "\f04b"; }
+
+.fa-font::before {
+  content: "\f031"; }
+
+.fa-rupiah-sign::before {
+  content: "\e23d"; }
+
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+  content: "\f002"; }
+
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+  content: "\f002"; }
+
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+  content: "\f45d"; }
+
+.fa-ping-pong-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-table-tennis::before {
+  content: "\f45d"; }
+
+.fa-person-dots-from-line::before {
+  content: "\f470"; }
+
+.fa-diagnoses::before {
+  content: "\f470"; }
+
+.fa-trash-can-arrow-up::before {
+  content: "\f82a"; }
+
+.fa-trash-restore-alt::before {
+  content: "\f82a"; }
+
+.fa-naira-sign::before {
+  content: "\e1f6"; }
+
+.fa-cart-arrow-down::before {
+  content: "\f218"; }
+
+.fa-walkie-talkie::before {
+  content: "\f8ef"; }
+
+.fa-file-pen::before {
+  content: "\f31c"; }
+
+.fa-file-edit::before {
+  content: "\f31c"; }
+
+.fa-receipt::before {
+  content: "\f543"; }
+
+.fa-square-pen::before {
+  content: "\f14b"; }
+
+.fa-pen-square::before {
+  content: "\f14b"; }
+
+.fa-pencil-square::before {
+  content: "\f14b"; }
+
+.fa-suitcase-rolling::before {
+  content: "\f5c1"; }
+
+.fa-person-circle-exclamation::before {
+  content: "\e53f"; }
+
+.fa-chevron-down::before {
+  content: "\f078"; }
+
+.fa-battery-full::before {
+  content: "\f240"; }
+
+.fa-battery::before {
+  content: "\f240"; }
+
+.fa-battery-5::before {
+  content: "\f240"; }
+
+.fa-skull-crossbones::before {
+  content: "\f714"; }
+
+.fa-code-compare::before {
+  content: "\e13a"; }
+
+.fa-list-ul::before {
+  content: "\f0ca"; }
+
+.fa-list-dots::before {
+  content: "\f0ca"; }
+
+.fa-school-lock::before {
+  content: "\e56f"; }
+
+.fa-tower-cell::before {
+  content: "\e585"; }
+
+.fa-down-long::before {
+  content: "\f309"; }
+
+.fa-long-arrow-alt-down::before {
+  content: "\f309"; }
+
+.fa-ranking-star::before {
+  content: "\e561"; }
+
+.fa-chess-king::before {
+  content: "\f43f"; }
+
+.fa-person-harassing::before {
+  content: "\e549"; }
+
+.fa-brazilian-real-sign::before {
+  content: "\e46c"; }
+
+.fa-landmark-dome::before {
+  content: "\f752"; }
+
+.fa-landmark-alt::before {
+  content: "\f752"; }
+
+.fa-arrow-up::before {
+  content: "\f062"; }
+
+.fa-tv::before {
+  content: "\f26c"; }
+
+.fa-television::before {
+  content: "\f26c"; }
+
+.fa-tv-alt::before {
+  content: "\f26c"; }
+
+.fa-shrimp::before {
+  content: "\e448"; }
+
+.fa-list-check::before {
+  content: "\f0ae"; }
+
+.fa-tasks::before {
+  content: "\f0ae"; }
+
+.fa-jug-detergent::before {
+  content: "\e519"; }
+
+.fa-circle-user::before {
+  content: "\f2bd"; }
+
+.fa-user-circle::before {
+  content: "\f2bd"; }
+
+.fa-user-shield::before {
+  content: "\f505"; }
+
+.fa-wind::before {
+  content: "\f72e"; }
+
+.fa-car-burst::before {
+  content: "\f5e1"; }
+
+.fa-car-crash::before {
+  content: "\f5e1"; }
+
+.fa-y::before {
+  content: "\59"; }
+
+.fa-person-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-truck-fast::before {
+  content: "\f48b"; }
+
+.fa-shipping-fast::before {
+  content: "\f48b"; }
+
+.fa-fish::before {
+  content: "\f578"; }
+
+.fa-user-graduate::before {
+  content: "\f501"; }
+
+.fa-circle-half-stroke::before {
+  content: "\f042"; }
+
+.fa-adjust::before {
+  content: "\f042"; }
+
+.fa-clapperboard::before {
+  content: "\e131"; }
+
+.fa-circle-radiation::before {
+  content: "\f7ba"; }
+
+.fa-radiation-alt::before {
+  content: "\f7ba"; }
+
+.fa-baseball::before {
+  content: "\f433"; }
+
+.fa-baseball-ball::before {
+  content: "\f433"; }
+
+.fa-jet-fighter-up::before {
+  content: "\e518"; }
+
+.fa-diagram-project::before {
+  content: "\f542"; }
+
+.fa-project-diagram::before {
+  content: "\f542"; }
+
+.fa-copy::before {
+  content: "\f0c5"; }
+
+.fa-volume-xmark::before {
+  content: "\f6a9"; }
+
+.fa-volume-mute::before {
+  content: "\f6a9"; }
+
+.fa-volume-times::before {
+  content: "\f6a9"; }
+
+.fa-hand-sparkles::before {
+  content: "\e05d"; }
+
+.fa-grip::before {
+  content: "\f58d"; }
+
+.fa-grip-horizontal::before {
+  content: "\f58d"; }
+
+.fa-share-from-square::before {
+  content: "\f14d"; }
+
+.fa-share-square::before {
+  content: "\f14d"; }
+
+.fa-child-combatant::before {
+  content: "\e4e0"; }
+
+.fa-child-rifle::before {
+  content: "\e4e0"; }
+
+.fa-gun::before {
+  content: "\e19b"; }
+
+.fa-square-phone::before {
+  content: "\f098"; }
+
+.fa-phone-square::before {
+  content: "\f098"; }
+
+.fa-plus::before {
+  content: "\2b"; }
+
+.fa-add::before {
+  content: "\2b"; }
+
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+  content: "\f065"; }
+
+.fa-computer::before {
+  content: "\e4e5"; }
+
+.fa-xmark::before {
+  content: "\f00d"; }
+
+.fa-close::before {
+  content: "\f00d"; }
+
+.fa-multiply::before {
+  content: "\f00d"; }
+
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+  content: "\f00d"; }
+
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+  content: "\f00d"; }
+
+.fa-arrows-up-down-left-right::before {
+  content: "\f047"; }
+
+.fa-arrows::before {
+  content: "\f047"; }
+
+.fa-chalkboard-user::before {
+  content: "\f51c"; }
+
+.fa-chalkboard-teacher::before {
+  content: "\f51c"; }
+
+.fa-peso-sign::before {
+  content: "\e222"; }
+
+.fa-building-shield::before {
+  content: "\e4d8"; }
+
+.fa-baby::before {
+  content: "\f77c"; }
+
+.fa-users-line::before {
+  content: "\e592"; }
+
+.fa-quote-left::before {
+  content: "\f10d"; }
+
+.fa-quote-left-alt::before {
+  content: "\f10d"; }
+
+.fa-tractor::before {
+  content: "\f722"; }
+
+.fa-trash-arrow-up::before {
+  content: "\f829"; }
+
+.fa-trash-restore::before {
+  content: "\f829"; }
+
+.fa-arrow-down-up-lock::before {
+  content: "\e4b0"; }
+
+.fa-lines-leaning::before {
+  content: "\e51e"; }
+
+.fa-ruler-combined::before {
+  content: "\f546"; }
+
+.fa-copyright::before {
+  content: "\f1f9"; }
+
+.fa-equals::before {
+  content: "\3d"; }
+
+.fa-blender::before {
+  content: "\f517"; }
+
+.fa-teeth::before {
+  content: "\f62e"; }
+
+.fa-shekel-sign::before {
+  content: "\f20b"; }
+
+.fa-ils::before {
+  content: "\f20b"; }
+
+.fa-shekel::before {
+  content: "\f20b"; }
+
+.fa-sheqel::before {
+  content: "\f20b"; }
+
+.fa-sheqel-sign::before {
+  content: "\f20b"; }
+
+.fa-map::before {
+  content: "\f279"; }
+
+.fa-rocket::before {
+  content: "\f135"; }
+
+.fa-photo-film::before {
+  content: "\f87c"; }
+
+.fa-photo-video::before {
+  content: "\f87c"; }
+
+.fa-folder-minus::before {
+  content: "\f65d"; }
+
+.fa-store::before {
+  content: "\f54e"; }
+
+.fa-arrow-trend-up::before {
+  content: "\e098"; }
+
+.fa-plug-circle-minus::before {
+  content: "\e55e"; }
+
+.fa-sign-hanging::before {
+  content: "\f4d9"; }
+
+.fa-sign::before {
+  content: "\f4d9"; }
+
+.fa-bezier-curve::before {
+  content: "\f55b"; }
+
+.fa-bell-slash::before {
+  content: "\f1f6"; }
+
+.fa-tablet::before {
+  content: "\f3fb"; }
+
+.fa-tablet-android::before {
+  content: "\f3fb"; }
+
+.fa-school-flag::before {
+  content: "\e56e"; }
+
+.fa-fill::before {
+  content: "\f575"; }
+
+.fa-angle-up::before {
+  content: "\f106"; }
+
+.fa-drumstick-bite::before {
+  content: "\f6d7"; }
+
+.fa-holly-berry::before {
+  content: "\f7aa"; }
+
+.fa-chevron-left::before {
+  content: "\f053"; }
+
+.fa-bacteria::before {
+  content: "\e059"; }
+
+.fa-hand-lizard::before {
+  content: "\f258"; }
+
+.fa-notdef::before {
+  content: "\e1fe"; }
+
+.fa-disease::before {
+  content: "\f7fa"; }
+
+.fa-briefcase-medical::before {
+  content: "\f469"; }
+
+.fa-genderless::before {
+  content: "\f22d"; }
+
+.fa-chevron-right::before {
+  content: "\f054"; }
+
+.fa-retweet::before {
+  content: "\f079"; }
+
+.fa-car-rear::before {
+  content: "\f5de"; }
+
+.fa-car-alt::before {
+  content: "\f5de"; }
+
+.fa-pump-soap::before {
+  content: "\e06b"; }
+
+.fa-video-slash::before {
+  content: "\f4e2"; }
+
+.fa-battery-quarter::before {
+  content: "\f243"; }
+
+.fa-battery-2::before {
+  content: "\f243"; }
+
+.fa-radio::before {
+  content: "\f8d7"; }
+
+.fa-baby-carriage::before {
+  content: "\f77d"; }
+
+.fa-carriage-baby::before {
+  content: "\f77d"; }
+
+.fa-traffic-light::before {
+  content: "\f637"; }
+
+.fa-thermometer::before {
+  content: "\f491"; }
+
+.fa-vr-cardboard::before {
+  content: "\f729"; }
+
+.fa-hand-middle-finger::before {
+  content: "\f806"; }
+
+.fa-percent::before {
+  content: "\25"; }
+
+.fa-percentage::before {
+  content: "\25"; }
+
+.fa-truck-moving::before {
+  content: "\f4df"; }
+
+.fa-glass-water-droplet::before {
+  content: "\e4f5"; }
+
+.fa-display::before {
+  content: "\e163"; }
+
+.fa-face-smile::before {
+  content: "\f118"; }
+
+.fa-smile::before {
+  content: "\f118"; }
+
+.fa-thumbtack::before {
+  content: "\f08d"; }
+
+.fa-thumb-tack::before {
+  content: "\f08d"; }
+
+.fa-trophy::before {
+  content: "\f091"; }
+
+.fa-person-praying::before {
+  content: "\f683"; }
+
+.fa-pray::before {
+  content: "\f683"; }
+
+.fa-hammer::before {
+  content: "\f6e3"; }
+
+.fa-hand-peace::before {
+  content: "\f25b"; }
+
+.fa-rotate::before {
+  content: "\f2f1"; }
+
+.fa-sync-alt::before {
+  content: "\f2f1"; }
+
+.fa-spinner::before {
+  content: "\f110"; }
+
+.fa-robot::before {
+  content: "\f544"; }
+
+.fa-peace::before {
+  content: "\f67c"; }
+
+.fa-gears::before {
+  content: "\f085"; }
+
+.fa-cogs::before {
+  content: "\f085"; }
+
+.fa-warehouse::before {
+  content: "\f494"; }
+
+.fa-arrow-up-right-dots::before {
+  content: "\e4b7"; }
+
+.fa-splotch::before {
+  content: "\f5bc"; }
+
+.fa-face-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-dice-four::before {
+  content: "\f524"; }
+
+.fa-sim-card::before {
+  content: "\f7c4"; }
+
+.fa-transgender::before {
+  content: "\f225"; }
+
+.fa-transgender-alt::before {
+  content: "\f225"; }
+
+.fa-mercury::before {
+  content: "\f223"; }
+
+.fa-arrow-turn-down::before {
+  content: "\f149"; }
+
+.fa-level-down::before {
+  content: "\f149"; }
+
+.fa-person-falling-burst::before {
+  content: "\e547"; }
+
+.fa-award::before {
+  content: "\f559"; }
+
+.fa-ticket-simple::before {
+  content: "\f3ff"; }
+
+.fa-ticket-alt::before {
+  content: "\f3ff"; }
+
+.fa-building::before {
+  content: "\f1ad"; }
+
+.fa-angles-left::before {
+  content: "\f100"; }
+
+.fa-angle-double-left::before {
+  content: "\f100"; }
+
+.fa-qrcode::before {
+  content: "\f029"; }
+
+.fa-clock-rotate-left::before {
+  content: "\f1da"; }
+
+.fa-history::before {
+  content: "\f1da"; }
+
+.fa-face-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-file-export::before {
+  content: "\f56e"; }
+
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+  content: "\f56e"; }
+
+.fa-shield::before {
+  content: "\f132"; }
+
+.fa-shield-blank::before {
+  content: "\f132"; }
+
+.fa-arrow-up-short-wide::before {
+  content: "\f885"; }
+
+.fa-sort-amount-up-alt::before {
+  content: "\f885"; }
+
+.fa-house-medical::before {
+  content: "\e3b2"; }
+
+.fa-golf-ball-tee::before {
+  content: "\f450"; }
+
+.fa-golf-ball::before {
+  content: "\f450"; }
+
+.fa-circle-chevron-left::before {
+  content: "\f137"; }
+
+.fa-chevron-circle-left::before {
+  content: "\f137"; }
+
+.fa-house-chimney-window::before {
+  content: "\e00d"; }
+
+.fa-pen-nib::before {
+  content: "\f5ad"; }
+
+.fa-tent-arrow-turn-left::before {
+  content: "\e580"; }
+
+.fa-tents::before {
+  content: "\e582"; }
+
+.fa-wand-magic::before {
+  content: "\f0d0"; }
+
+.fa-magic::before {
+  content: "\f0d0"; }
+
+.fa-dog::before {
+  content: "\f6d3"; }
+
+.fa-carrot::before {
+  content: "\f787"; }
+
+.fa-moon::before {
+  content: "\f186"; }
+
+.fa-wine-glass-empty::before {
+  content: "\f5ce"; }
+
+.fa-wine-glass-alt::before {
+  content: "\f5ce"; }
+
+.fa-cheese::before {
+  content: "\f7ef"; }
+
+.fa-yin-yang::before {
+  content: "\f6ad"; }
+
+.fa-music::before {
+  content: "\f001"; }
+
+.fa-code-commit::before {
+  content: "\f386"; }
+
+.fa-temperature-low::before {
+  content: "\f76b"; }
+
+.fa-person-biking::before {
+  content: "\f84a"; }
+
+.fa-biking::before {
+  content: "\f84a"; }
+
+.fa-broom::before {
+  content: "\f51a"; }
+
+.fa-shield-heart::before {
+  content: "\e574"; }
+
+.fa-gopuram::before {
+  content: "\f664"; }
+
+.fa-earth-oceania::before {
+  content: "\e47b"; }
+
+.fa-globe-oceania::before {
+  content: "\e47b"; }
+
+.fa-square-xmark::before {
+  content: "\f2d3"; }
+
+.fa-times-square::before {
+  content: "\f2d3"; }
+
+.fa-xmark-square::before {
+  content: "\f2d3"; }
+
+.fa-hashtag::before {
+  content: "\23"; }
+
+.fa-up-right-and-down-left-from-center::before {
+  content: "\f424"; }
+
+.fa-expand-alt::before {
+  content: "\f424"; }
+
+.fa-oil-can::before {
+  content: "\f613"; }
+
+.fa-t::before {
+  content: "\54"; }
+
+.fa-hippo::before {
+  content: "\f6ed"; }
+
+.fa-chart-column::before {
+  content: "\e0e3"; }
+
+.fa-infinity::before {
+  content: "\f534"; }
+
+.fa-vial-circle-check::before {
+  content: "\e596"; }
+
+.fa-person-arrow-down-to-line::before {
+  content: "\e538"; }
+
+.fa-voicemail::before {
+  content: "\f897"; }
+
+.fa-fan::before {
+  content: "\f863"; }
+
+.fa-person-walking-luggage::before {
+  content: "\e554"; }
+
+.fa-up-down::before {
+  content: "\f338"; }
+
+.fa-arrows-alt-v::before {
+  content: "\f338"; }
+
+.fa-cloud-moon-rain::before {
+  content: "\f73c"; }
+
+.fa-calendar::before {
+  content: "\f133"; }
+
+.fa-trailer::before {
+  content: "\e041"; }
+
+.fa-bahai::before {
+  content: "\f666"; }
+
+.fa-haykal::before {
+  content: "\f666"; }
+
+.fa-sd-card::before {
+  content: "\f7c2"; }
+
+.fa-dragon::before {
+  content: "\f6d5"; }
+
+.fa-shoe-prints::before {
+  content: "\f54b"; }
+
+.fa-circle-plus::before {
+  content: "\f055"; }
+
+.fa-plus-circle::before {
+  content: "\f055"; }
+
+.fa-face-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-hand-holding::before {
+  content: "\f4bd"; }
+
+.fa-plug-circle-exclamation::before {
+  content: "\e55d"; }
+
+.fa-link-slash::before {
+  content: "\f127"; }
+
+.fa-chain-broken::before {
+  content: "\f127"; }
+
+.fa-chain-slash::before {
+  content: "\f127"; }
+
+.fa-unlink::before {
+  content: "\f127"; }
+
+.fa-clone::before {
+  content: "\f24d"; }
+
+.fa-person-walking-arrow-loop-left::before {
+  content: "\e551"; }
+
+.fa-arrow-up-z-a::before {
+  content: "\f882"; }
+
+.fa-sort-alpha-up-alt::before {
+  content: "\f882"; }
+
+.fa-fire-flame-curved::before {
+  content: "\f7e4"; }
+
+.fa-fire-alt::before {
+  content: "\f7e4"; }
+
+.fa-tornado::before {
+  content: "\f76f"; }
+
+.fa-file-circle-plus::before {
+  content: "\e494"; }
+
+.fa-book-quran::before {
+  content: "\f687"; }
+
+.fa-quran::before {
+  content: "\f687"; }
+
+.fa-anchor::before {
+  content: "\f13d"; }
+
+.fa-border-all::before {
+  content: "\f84c"; }
+
+.fa-face-angry::before {
+  content: "\f556"; }
+
+.fa-angry::before {
+  content: "\f556"; }
+
+.fa-cookie-bite::before {
+  content: "\f564"; }
+
+.fa-arrow-trend-down::before {
+  content: "\e097"; }
+
+.fa-rss::before {
+  content: "\f09e"; }
+
+.fa-feed::before {
+  content: "\f09e"; }
+
+.fa-draw-polygon::before {
+  content: "\f5ee"; }
+
+.fa-scale-balanced::before {
+  content: "\f24e"; }
+
+.fa-balance-scale::before {
+  content: "\f24e"; }
+
+.fa-gauge-simple-high::before {
+  content: "\f62a"; }
+
+.fa-tachometer::before {
+  content: "\f62a"; }
+
+.fa-tachometer-fast::before {
+  content: "\f62a"; }
+
+.fa-shower::before {
+  content: "\f2cc"; }
+
+.fa-desktop::before {
+  content: "\f390"; }
+
+.fa-desktop-alt::before {
+  content: "\f390"; }
+
+.fa-m::before {
+  content: "\4d"; }
+
+.fa-table-list::before {
+  content: "\f00b"; }
+
+.fa-th-list::before {
+  content: "\f00b"; }
+
+.fa-comment-sms::before {
+  content: "\f7cd"; }
+
+.fa-sms::before {
+  content: "\f7cd"; }
+
+.fa-book::before {
+  content: "\f02d"; }
+
+.fa-user-plus::before {
+  content: "\f234"; }
+
+.fa-check::before {
+  content: "\f00c"; }
+
+.fa-battery-three-quarters::before {
+  content: "\f241"; }
+
+.fa-battery-4::before {
+  content: "\f241"; }
+
+.fa-house-circle-check::before {
+  content: "\e509"; }
+
+.fa-angle-left::before {
+  content: "\f104"; }
+
+.fa-diagram-successor::before {
+  content: "\e47a"; }
+
+.fa-truck-arrow-right::before {
+  content: "\e58b"; }
+
+.fa-arrows-split-up-and-left::before {
+  content: "\e4bc"; }
+
+.fa-hand-fist::before {
+  content: "\f6de"; }
+
+.fa-fist-raised::before {
+  content: "\f6de"; }
+
+.fa-cloud-moon::before {
+  content: "\f6c3"; }
+
+.fa-briefcase::before {
+  content: "\f0b1"; }
+
+.fa-person-falling::before {
+  content: "\e546"; }
+
+.fa-image-portrait::before {
+  content: "\f3e0"; }
+
+.fa-portrait::before {
+  content: "\f3e0"; }
+
+.fa-user-tag::before {
+  content: "\f507"; }
+
+.fa-rug::before {
+  content: "\e569"; }
+
+.fa-earth-europe::before {
+  content: "\f7a2"; }
+
+.fa-globe-europe::before {
+  content: "\f7a2"; }
+
+.fa-cart-flatbed-suitcase::before {
+  content: "\f59d"; }
+
+.fa-luggage-cart::before {
+  content: "\f59d"; }
+
+.fa-rectangle-xmark::before {
+  content: "\f410"; }
+
+.fa-rectangle-times::before {
+  content: "\f410"; }
+
+.fa-times-rectangle::before {
+  content: "\f410"; }
+
+.fa-window-close::before {
+  content: "\f410"; }
+
+.fa-baht-sign::before {
+  content: "\e0ac"; }
+
+.fa-book-open::before {
+  content: "\f518"; }
+
+.fa-book-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-handcuffs::before {
+  content: "\e4f8"; }
+
+.fa-triangle-exclamation::before {
+  content: "\f071"; }
+
+.fa-exclamation-triangle::before {
+  content: "\f071"; }
+
+.fa-warning::before {
+  content: "\f071"; }
+
+.fa-database::before {
+  content: "\f1c0"; }
+
+.fa-share::before {
+  content: "\f064"; }
+
+.fa-arrow-turn-right::before {
+  content: "\f064"; }
+
+.fa-mail-forward::before {
+  content: "\f064"; }
+
+.fa-bottle-droplet::before {
+  content: "\e4c4"; }
+
+.fa-mask-face::before {
+  content: "\e1d7"; }
+
+.fa-hill-rockslide::before {
+  content: "\e508"; }
+
+.fa-right-left::before {
+  content: "\f362"; }
+
+.fa-exchange-alt::before {
+  content: "\f362"; }
+
+.fa-paper-plane::before {
+  content: "\f1d8"; }
+
+.fa-road-circle-exclamation::before {
+  content: "\e565"; }
+
+.fa-dungeon::before {
+  content: "\f6d9"; }
+
+.fa-align-right::before {
+  content: "\f038"; }
+
+.fa-money-bill-1-wave::before {
+  content: "\f53b"; }
+
+.fa-money-bill-wave-alt::before {
+  content: "\f53b"; }
+
+.fa-life-ring::before {
+  content: "\f1cd"; }
+
+.fa-hands::before {
+  content: "\f2a7"; }
+
+.fa-sign-language::before {
+  content: "\f2a7"; }
+
+.fa-signing::before {
+  content: "\f2a7"; }
+
+.fa-calendar-day::before {
+  content: "\f783"; }
+
+.fa-water-ladder::before {
+  content: "\f5c5"; }
+
+.fa-ladder-water::before {
+  content: "\f5c5"; }
+
+.fa-swimming-pool::before {
+  content: "\f5c5"; }
+
+.fa-arrows-up-down::before {
+  content: "\f07d"; }
+
+.fa-arrows-v::before {
+  content: "\f07d"; }
+
+.fa-face-grimace::before {
+  content: "\f57f"; }
+
+.fa-grimace::before {
+  content: "\f57f"; }
+
+.fa-wheelchair-move::before {
+  content: "\e2ce"; }
+
+.fa-wheelchair-alt::before {
+  content: "\e2ce"; }
+
+.fa-turn-down::before {
+  content: "\f3be"; }
+
+.fa-level-down-alt::before {
+  content: "\f3be"; }
+
+.fa-person-walking-arrow-right::before {
+  content: "\e552"; }
+
+.fa-square-envelope::before {
+  content: "\f199"; }
+
+.fa-envelope-square::before {
+  content: "\f199"; }
+
+.fa-dice::before {
+  content: "\f522"; }
+
+.fa-bowling-ball::before {
+  content: "\f436"; }
+
+.fa-brain::before {
+  content: "\f5dc"; }
+
+.fa-bandage::before {
+  content: "\f462"; }
+
+.fa-band-aid::before {
+  content: "\f462"; }
+
+.fa-calendar-minus::before {
+  content: "\f272"; }
+
+.fa-circle-xmark::before {
+  content: "\f057"; }
+
+.fa-times-circle::before {
+  content: "\f057"; }
+
+.fa-xmark-circle::before {
+  content: "\f057"; }
+
+.fa-gifts::before {
+  content: "\f79c"; }
+
+.fa-hotel::before {
+  content: "\f594"; }
+
+.fa-earth-asia::before {
+  content: "\f57e"; }
+
+.fa-globe-asia::before {
+  content: "\f57e"; }
+
+.fa-id-card-clip::before {
+  content: "\f47f"; }
+
+.fa-id-card-alt::before {
+  content: "\f47f"; }
+
+.fa-magnifying-glass-plus::before {
+  content: "\f00e"; }
+
+.fa-search-plus::before {
+  content: "\f00e"; }
+
+.fa-thumbs-up::before {
+  content: "\f164"; }
+
+.fa-user-clock::before {
+  content: "\f4fd"; }
+
+.fa-hand-dots::before {
+  content: "\f461"; }
+
+.fa-allergies::before {
+  content: "\f461"; }
+
+.fa-file-invoice::before {
+  content: "\f570"; }
+
+.fa-window-minimize::before {
+  content: "\f2d1"; }
+
+.fa-mug-saucer::before {
+  content: "\f0f4"; }
+
+.fa-coffee::before {
+  content: "\f0f4"; }
+
+.fa-brush::before {
+  content: "\f55d"; }
+
+.fa-mask::before {
+  content: "\f6fa"; }
+
+.fa-magnifying-glass-minus::before {
+  content: "\f010"; }
+
+.fa-search-minus::before {
+  content: "\f010"; }
+
+.fa-ruler-vertical::before {
+  content: "\f548"; }
+
+.fa-user-large::before {
+  content: "\f406"; }
+
+.fa-user-alt::before {
+  content: "\f406"; }
+
+.fa-train-tram::before {
+  content: "\e5b4"; }
+
+.fa-user-nurse::before {
+  content: "\f82f"; }
+
+.fa-syringe::before {
+  content: "\f48e"; }
+
+.fa-cloud-sun::before {
+  content: "\f6c4"; }
+
+.fa-stopwatch-20::before {
+  content: "\e06f"; }
+
+.fa-square-full::before {
+  content: "\f45c"; }
+
+.fa-magnet::before {
+  content: "\f076"; }
+
+.fa-jar::before {
+  content: "\e516"; }
+
+.fa-note-sticky::before {
+  content: "\f249"; }
+
+.fa-sticky-note::before {
+  content: "\f249"; }
+
+.fa-bug-slash::before {
+  content: "\e490"; }
+
+.fa-arrow-up-from-water-pump::before {
+  content: "\e4b6"; }
+
+.fa-bone::before {
+  content: "\f5d7"; }
+
+.fa-user-injured::before {
+  content: "\f728"; }
+
+.fa-face-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-plane::before {
+  content: "\f072"; }
+
+.fa-tent-arrows-down::before {
+  content: "\e581"; }
+
+.fa-exclamation::before {
+  content: "\21"; }
+
+.fa-arrows-spin::before {
+  content: "\e4bb"; }
+
+.fa-print::before {
+  content: "\f02f"; }
+
+.fa-turkish-lira-sign::before {
+  content: "\e2bb"; }
+
+.fa-try::before {
+  content: "\e2bb"; }
+
+.fa-turkish-lira::before {
+  content: "\e2bb"; }
+
+.fa-dollar-sign::before {
+  content: "\24"; }
+
+.fa-dollar::before {
+  content: "\24"; }
+
+.fa-usd::before {
+  content: "\24"; }
+
+.fa-x::before {
+  content: "\58"; }
+
+.fa-magnifying-glass-dollar::before {
+  content: "\f688"; }
+
+.fa-search-dollar::before {
+  content: "\f688"; }
+
+.fa-users-gear::before {
+  content: "\f509"; }
+
+.fa-users-cog::before {
+  content: "\f509"; }
+
+.fa-person-military-pointing::before {
+  content: "\e54a"; }
+
+.fa-building-columns::before {
+  content: "\f19c"; }
+
+.fa-bank::before {
+  content: "\f19c"; }
+
+.fa-institution::before {
+  content: "\f19c"; }
+
+.fa-museum::before {
+  content: "\f19c"; }
+
+.fa-university::before {
+  content: "\f19c"; }
+
+.fa-umbrella::before {
+  content: "\f0e9"; }
+
+.fa-trowel::before {
+  content: "\e589"; }
+
+.fa-d::before {
+  content: "\44"; }
+
+.fa-stapler::before {
+  content: "\e5af"; }
+
+.fa-masks-theater::before {
+  content: "\f630"; }
+
+.fa-theater-masks::before {
+  content: "\f630"; }
+
+.fa-kip-sign::before {
+  content: "\e1c4"; }
+
+.fa-hand-point-left::before {
+  content: "\f0a5"; }
+
+.fa-handshake-simple::before {
+  content: "\f4c6"; }
+
+.fa-handshake-alt::before {
+  content: "\f4c6"; }
+
+.fa-jet-fighter::before {
+  content: "\f0fb"; }
+
+.fa-fighter-jet::before {
+  content: "\f0fb"; }
+
+.fa-square-share-nodes::before {
+  content: "\f1e1"; }
+
+.fa-share-alt-square::before {
+  content: "\f1e1"; }
+
+.fa-barcode::before {
+  content: "\f02a"; }
+
+.fa-plus-minus::before {
+  content: "\e43c"; }
+
+.fa-video::before {
+  content: "\f03d"; }
+
+.fa-video-camera::before {
+  content: "\f03d"; }
+
+.fa-graduation-cap::before {
+  content: "\f19d"; }
+
+.fa-mortar-board::before {
+  content: "\f19d"; }
+
+.fa-hand-holding-medical::before {
+  content: "\e05c"; }
+
+.fa-person-circle-check::before {
+  content: "\e53e"; }
+
+.fa-turn-up::before {
+  content: "\f3bf"; }
+
+.fa-level-up-alt::before {
+  content: "\f3bf"; }
+
+.sr-only,
+.fa-sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+
+.sr-only-focusable:not(:focus),
+.fa-sr-only-focusable:not(:focus) {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+:root, :host {
+  --fa-style-family-brands: 'Font Awesome 6 Brands';
+  --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Brands';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+.fab,
+.fa-brands {
+  font-weight: 400; }
+
+.fa-monero:before {
+  content: "\f3d0"; }
+
+.fa-hooli:before {
+  content: "\f427"; }
+
+.fa-yelp:before {
+  content: "\f1e9"; }
+
+.fa-cc-visa:before {
+  content: "\f1f0"; }
+
+.fa-lastfm:before {
+  content: "\f202"; }
+
+.fa-shopware:before {
+  content: "\f5b5"; }
+
+.fa-creative-commons-nc:before {
+  content: "\f4e8"; }
+
+.fa-aws:before {
+  content: "\f375"; }
+
+.fa-redhat:before {
+  content: "\f7bc"; }
+
+.fa-yoast:before {
+  content: "\f2b1"; }
+
+.fa-cloudflare:before {
+  content: "\e07d"; }
+
+.fa-ups:before {
+  content: "\f7e0"; }
+
+.fa-wpexplorer:before {
+  content: "\f2de"; }
+
+.fa-dyalog:before {
+  content: "\f399"; }
+
+.fa-bity:before {
+  content: "\f37a"; }
+
+.fa-stackpath:before {
+  content: "\f842"; }
+
+.fa-buysellads:before {
+  content: "\f20d"; }
+
+.fa-first-order:before {
+  content: "\f2b0"; }
+
+.fa-modx:before {
+  content: "\f285"; }
+
+.fa-guilded:before {
+  content: "\e07e"; }
+
+.fa-vnv:before {
+  content: "\f40b"; }
+
+.fa-square-js:before {
+  content: "\f3b9"; }
+
+.fa-js-square:before {
+  content: "\f3b9"; }
+
+.fa-microsoft:before {
+  content: "\f3ca"; }
+
+.fa-qq:before {
+  content: "\f1d6"; }
+
+.fa-orcid:before {
+  content: "\f8d2"; }
+
+.fa-java:before {
+  content: "\f4e4"; }
+
+.fa-invision:before {
+  content: "\f7b0"; }
+
+.fa-creative-commons-pd-alt:before {
+  content: "\f4ed"; }
+
+.fa-centercode:before {
+  content: "\f380"; }
+
+.fa-glide-g:before {
+  content: "\f2a6"; }
+
+.fa-drupal:before {
+  content: "\f1a9"; }
+
+.fa-hire-a-helper:before {
+  content: "\f3b0"; }
+
+.fa-creative-commons-by:before {
+  content: "\f4e7"; }
+
+.fa-unity:before {
+  content: "\e049"; }
+
+.fa-whmcs:before {
+  content: "\f40d"; }
+
+.fa-rocketchat:before {
+  content: "\f3e8"; }
+
+.fa-vk:before {
+  content: "\f189"; }
+
+.fa-untappd:before {
+  content: "\f405"; }
+
+.fa-mailchimp:before {
+  content: "\f59e"; }
+
+.fa-css3-alt:before {
+  content: "\f38b"; }
+
+.fa-square-reddit:before {
+  content: "\f1a2"; }
+
+.fa-reddit-square:before {
+  content: "\f1a2"; }
+
+.fa-vimeo-v:before {
+  content: "\f27d"; }
+
+.fa-contao:before {
+  content: "\f26d"; }
+
+.fa-square-font-awesome:before {
+  content: "\e5ad"; }
+
+.fa-deskpro:before {
+  content: "\f38f"; }
+
+.fa-sistrix:before {
+  content: "\f3ee"; }
+
+.fa-square-instagram:before {
+  content: "\e055"; }
+
+.fa-instagram-square:before {
+  content: "\e055"; }
+
+.fa-battle-net:before {
+  content: "\f835"; }
+
+.fa-the-red-yeti:before {
+  content: "\f69d"; }
+
+.fa-square-hacker-news:before {
+  content: "\f3af"; }
+
+.fa-hacker-news-square:before {
+  content: "\f3af"; }
+
+.fa-edge:before {
+  content: "\f282"; }
+
+.fa-threads:before {
+  content: "\e618"; }
+
+.fa-napster:before {
+  content: "\f3d2"; }
+
+.fa-square-snapchat:before {
+  content: "\f2ad"; }
+
+.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa-google-plus-g:before {
+  content: "\f0d5"; }
+
+.fa-artstation:before {
+  content: "\f77a"; }
+
+.fa-markdown:before {
+  content: "\f60f"; }
+
+.fa-sourcetree:before {
+  content: "\f7d3"; }
+
+.fa-google-plus:before {
+  content: "\f2b3"; }
+
+.fa-diaspora:before {
+  content: "\f791"; }
+
+.fa-foursquare:before {
+  content: "\f180"; }
+
+.fa-stack-overflow:before {
+  content: "\f16c"; }
+
+.fa-github-alt:before {
+  content: "\f113"; }
+
+.fa-phoenix-squadron:before {
+  content: "\f511"; }
+
+.fa-pagelines:before {
+  content: "\f18c"; }
+
+.fa-algolia:before {
+  content: "\f36c"; }
+
+.fa-red-river:before {
+  content: "\f3e3"; }
+
+.fa-creative-commons-sa:before {
+  content: "\f4ef"; }
+
+.fa-safari:before {
+  content: "\f267"; }
+
+.fa-google:before {
+  content: "\f1a0"; }
+
+.fa-square-font-awesome-stroke:before {
+  content: "\f35c"; }
+
+.fa-font-awesome-alt:before {
+  content: "\f35c"; }
+
+.fa-atlassian:before {
+  content: "\f77b"; }
+
+.fa-linkedin-in:before {
+  content: "\f0e1"; }
+
+.fa-digital-ocean:before {
+  content: "\f391"; }
+
+.fa-nimblr:before {
+  content: "\f5a8"; }
+
+.fa-chromecast:before {
+  content: "\f838"; }
+
+.fa-evernote:before {
+  content: "\f839"; }
+
+.fa-hacker-news:before {
+  content: "\f1d4"; }
+
+.fa-creative-commons-sampling:before {
+  content: "\f4f0"; }
+
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+  content: "\f5cf"; }
+
+.fa-square-behance:before {
+  content: "\f1b5"; }
+
+.fa-behance-square:before {
+  content: "\f1b5"; }
+
+.fa-supple:before {
+  content: "\f3f9"; }
+
+.fa-rebel:before {
+  content: "\f1d0"; }
+
+.fa-css3:before {
+  content: "\f13c"; }
+
+.fa-staylinked:before {
+  content: "\f3f5"; }
+
+.fa-kaggle:before {
+  content: "\f5fa"; }
+
+.fa-space-awesome:before {
+  content: "\e5ac"; }
+
+.fa-deviantart:before {
+  content: "\f1bd"; }
+
+.fa-cpanel:before {
+  content: "\f388"; }
+
+.fa-goodreads-g:before {
+  content: "\f3a9"; }
+
+.fa-square-git:before {
+  content: "\f1d2"; }
+
+.fa-git-square:before {
+  content: "\f1d2"; }
+
+.fa-square-tumblr:before {
+  content: "\f174"; }
+
+.fa-tumblr-square:before {
+  content: "\f174"; }
+
+.fa-trello:before {
+  content: "\f181"; }
+
+.fa-creative-commons-nc-jp:before {
+  content: "\f4ea"; }
+
+.fa-get-pocket:before {
+  content: "\f265"; }
+
+.fa-perbyte:before {
+  content: "\e083"; }
+
+.fa-grunt:before {
+  content: "\f3ad"; }
+
+.fa-weebly:before {
+  content: "\f5cc"; }
+
+.fa-connectdevelop:before {
+  content: "\f20e"; }
+
+.fa-leanpub:before {
+  content: "\f212"; }
+
+.fa-black-tie:before {
+  content: "\f27e"; }
+
+.fa-themeco:before {
+  content: "\f5c6"; }
+
+.fa-python:before {
+  content: "\f3e2"; }
+
+.fa-android:before {
+  content: "\f17b"; }
+
+.fa-bots:before {
+  content: "\e340"; }
+
+.fa-free-code-camp:before {
+  content: "\f2c5"; }
+
+.fa-hornbill:before {
+  content: "\f592"; }
+
+.fa-js:before {
+  content: "\f3b8"; }
+
+.fa-ideal:before {
+  content: "\e013"; }
+
+.fa-git:before {
+  content: "\f1d3"; }
+
+.fa-dev:before {
+  content: "\f6cc"; }
+
+.fa-sketch:before {
+  content: "\f7c6"; }
+
+.fa-yandex-international:before {
+  content: "\f414"; }
+
+.fa-cc-amex:before {
+  content: "\f1f3"; }
+
+.fa-uber:before {
+  content: "\f402"; }
+
+.fa-github:before {
+  content: "\f09b"; }
+
+.fa-php:before {
+  content: "\f457"; }
+
+.fa-alipay:before {
+  content: "\f642"; }
+
+.fa-youtube:before {
+  content: "\f167"; }
+
+.fa-skyatlas:before {
+  content: "\f216"; }
+
+.fa-firefox-browser:before {
+  content: "\e007"; }
+
+.fa-replyd:before {
+  content: "\f3e6"; }
+
+.fa-suse:before {
+  content: "\f7d6"; }
+
+.fa-jenkins:before {
+  content: "\f3b6"; }
+
+.fa-twitter:before {
+  content: "\f099"; }
+
+.fa-rockrms:before {
+  content: "\f3e9"; }
+
+.fa-pinterest:before {
+  content: "\f0d2"; }
+
+.fa-buffer:before {
+  content: "\f837"; }
+
+.fa-npm:before {
+  content: "\f3d4"; }
+
+.fa-yammer:before {
+  content: "\f840"; }
+
+.fa-btc:before {
+  content: "\f15a"; }
+
+.fa-dribbble:before {
+  content: "\f17d"; }
+
+.fa-stumbleupon-circle:before {
+  content: "\f1a3"; }
+
+.fa-internet-explorer:before {
+  content: "\f26b"; }
+
+.fa-stubber:before {
+  content: "\e5c7"; }
+
+.fa-telegram:before {
+  content: "\f2c6"; }
+
+.fa-telegram-plane:before {
+  content: "\f2c6"; }
+
+.fa-old-republic:before {
+  content: "\f510"; }
+
+.fa-odysee:before {
+  content: "\e5c6"; }
+
+.fa-square-whatsapp:before {
+  content: "\f40c"; }
+
+.fa-whatsapp-square:before {
+  content: "\f40c"; }
+
+.fa-node-js:before {
+  content: "\f3d3"; }
+
+.fa-edge-legacy:before {
+  content: "\e078"; }
+
+.fa-slack:before {
+  content: "\f198"; }
+
+.fa-slack-hash:before {
+  content: "\f198"; }
+
+.fa-medrt:before {
+  content: "\f3c8"; }
+
+.fa-usb:before {
+  content: "\f287"; }
+
+.fa-tumblr:before {
+  content: "\f173"; }
+
+.fa-vaadin:before {
+  content: "\f408"; }
+
+.fa-quora:before {
+  content: "\f2c4"; }
+
+.fa-square-x-twitter:before {
+  content: "\e61a"; }
+
+.fa-reacteurope:before {
+  content: "\f75d"; }
+
+.fa-medium:before {
+  content: "\f23a"; }
+
+.fa-medium-m:before {
+  content: "\f23a"; }
+
+.fa-amilia:before {
+  content: "\f36d"; }
+
+.fa-mixcloud:before {
+  content: "\f289"; }
+
+.fa-flipboard:before {
+  content: "\f44d"; }
+
+.fa-viacoin:before {
+  content: "\f237"; }
+
+.fa-critical-role:before {
+  content: "\f6c9"; }
+
+.fa-sitrox:before {
+  content: "\e44a"; }
+
+.fa-discourse:before {
+  content: "\f393"; }
+
+.fa-joomla:before {
+  content: "\f1aa"; }
+
+.fa-mastodon:before {
+  content: "\f4f6"; }
+
+.fa-airbnb:before {
+  content: "\f834"; }
+
+.fa-wolf-pack-battalion:before {
+  content: "\f514"; }
+
+.fa-buy-n-large:before {
+  content: "\f8a6"; }
+
+.fa-gulp:before {
+  content: "\f3ae"; }
+
+.fa-creative-commons-sampling-plus:before {
+  content: "\f4f1"; }
+
+.fa-strava:before {
+  content: "\f428"; }
+
+.fa-ember:before {
+  content: "\f423"; }
+
+.fa-canadian-maple-leaf:before {
+  content: "\f785"; }
+
+.fa-teamspeak:before {
+  content: "\f4f9"; }
+
+.fa-pushed:before {
+  content: "\f3e1"; }
+
+.fa-wordpress-simple:before {
+  content: "\f411"; }
+
+.fa-nutritionix:before {
+  content: "\f3d6"; }
+
+.fa-wodu:before {
+  content: "\e088"; }
+
+.fa-google-pay:before {
+  content: "\e079"; }
+
+.fa-intercom:before {
+  content: "\f7af"; }
+
+.fa-zhihu:before {
+  content: "\f63f"; }
+
+.fa-korvue:before {
+  content: "\f42f"; }
+
+.fa-pix:before {
+  content: "\e43a"; }
+
+.fa-steam-symbol:before {
+  content: "\f3f6"; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-regular: normal 400 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+.far,
+.fa-regular {
+  font-weight: 400; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-solid: normal 900 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 900;
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+.fas,
+.fa-solid {
+  font-weight: 900; }
+@font-face {
+  font-family: 'Font Awesome 5 Brands';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 900;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-v4compatibility.woff2") format("woff2"), url("../webfonts/fa-v4compatibility.ttf") format("truetype"); }
diff --git a/deps/font-awesome-6.4.2/css/all.min.css b/deps/font-awesome-6.4.2/css/all.min.css
new file mode 100644
index 00000000..6604a067
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/all.min.css
@@ -0,0 +1,9 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa{font-family:var(--fa-style-family,"Font Awesome 6 Free");font-weight:var(--fa-style,900)}.fa,.fa-brands,.fa-classic,.fa-regular,.fa-sharp,.fa-solid,.fab,.far,.fas{-moz-osx-font-smoothing:grayscale;-webkit-font-smoothing:antialiased;display:var(--fa-display,inline-block);font-style:normal;font-variant:normal;line-height:1;text-rendering:auto}.fa-classic,.fa-regular,.fa-solid,.far,.fas{font-family:"Font Awesome 6 Free"}.fa-brands,.fab{font-family:"Font Awesome 6 Brands"}.fa-1x{font-size:1em}.fa-2x{font-size:2em}.fa-3x{font-size:3em}.fa-4x{font-size:4em}.fa-5x{font-size:5em}.fa-6x{font-size:6em}.fa-7x{font-size:7em}.fa-8x{font-size:8em}.fa-9x{font-size:9em}.fa-10x{font-size:10em}.fa-2xs{font-size:.625em;line-height:.1em;vertical-align:.225em}.fa-xs{font-size:.75em;line-height:.08333em;vertical-align:.125em}.fa-sm{font-size:.875em;line-height:.07143em;vertical-align:.05357em}.fa-lg{font-size:1.25em;line-height:.05em;vertical-align:-.075em}.fa-xl{font-size:1.5em;line-height:.04167em;vertical-align:-.125em}.fa-2xl{font-size:2em;line-height:.03125em;vertical-align:-.1875em}.fa-fw{text-align:center;width:1.25em}.fa-ul{list-style-type:none;margin-left:var(--fa-li-margin,2.5em);padding-left:0}.fa-ul>li{position:relative}.fa-li{left:calc(var(--fa-li-width, 2em)*-1);position:absolute;text-align:center;width:var(--fa-li-width,2em);line-height:inherit}.fa-border{border-radius:var(--fa-border-radius,.1em);border:var(--fa-border-width,.08em) var(--fa-border-style,solid) var(--fa-border-color,#eee);padding:var(--fa-border-padding,.2em .25em .15em)}.fa-pull-left{float:left;margin-right:var(--fa-pull-margin,.3em)}.fa-pull-right{float:right;margin-left:var(--fa-pull-margin,.3em)}.fa-beat{-webkit-animation-name:fa-beat;animation-name:fa-beat;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,ease-in-out);animation-timing-function:var(--fa-animation-timing,ease-in-out)}.fa-bounce{-webkit-animation-name:fa-bounce;animation-name:fa-bounce;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.28,.84,.42,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.28,.84,.42,1))}.fa-fade{-webkit-animation-name:fa-fade;animation-name:fa-fade;-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1))}.fa-beat-fade,.fa-fade{-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s)}.fa-beat-fade{-webkit-animation-name:fa-beat-fade;animation-name:fa-beat-fade;-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1))}.fa-flip{-webkit-animation-name:fa-flip;animation-name:fa-flip;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,ease-in-out);animation-timing-function:var(--fa-animation-timing,ease-in-out)}.fa-shake{-webkit-animation-name:fa-shake;animation-name:fa-shake;-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,linear);animation-timing-function:var(--fa-animation-timing,linear)}.fa-shake,.fa-spin{-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal)}.fa-spin{-webkit-animation-name:fa-spin;animation-name:fa-spin;-webkit-animation-duration:var(--fa-animation-duration,2s);animation-duration:var(--fa-animation-duration,2s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,linear);animation-timing-function:var(--fa-animation-timing,linear)}.fa-spin-reverse{--fa-animation-direction:reverse}.fa-pulse,.fa-spin-pulse{-webkit-animation-name:fa-spin;animation-name:fa-spin;-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,steps(8));animation-timing-function:var(--fa-animation-timing,steps(8))}@media (prefers-reduced-motion:reduce){.fa-beat,.fa-beat-fade,.fa-bounce,.fa-fade,.fa-flip,.fa-pulse,.fa-shake,.fa-spin,.fa-spin-pulse{-webkit-animation-delay:-1ms;animation-delay:-1ms;-webkit-animation-duration:1ms;animation-duration:1ms;-webkit-animation-iteration-count:1;animation-iteration-count:1;-webkit-transition-delay:0s;transition-delay:0s;-webkit-transition-duration:0s;transition-duration:0s}}@-webkit-keyframes fa-beat{0%,90%{-webkit-transform:scale(1);transform:scale(1)}45%{-webkit-transform:scale(var(--fa-beat-scale,1.25));transform:scale(var(--fa-beat-scale,1.25))}}@keyframes fa-beat{0%,90%{-webkit-transform:scale(1);transform:scale(1)}45%{-webkit-transform:scale(var(--fa-beat-scale,1.25));transform:scale(var(--fa-beat-scale,1.25))}}@-webkit-keyframes fa-bounce{0%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}10%{-webkit-transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0);transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0)}30%{-webkit-transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em));transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em))}50%{-webkit-transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0);transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0)}57%{-webkit-transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em));transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em))}64%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}to{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}}@keyframes fa-bounce{0%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}10%{-webkit-transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0);transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0)}30%{-webkit-transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em));transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em))}50%{-webkit-transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0);transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0)}57%{-webkit-transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em));transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em))}64%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}to{-webkit-transform:scale(1) translateY(0);transform:scale(1) 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\ No newline at end of file
diff --git a/deps/font-awesome-6.4.2/css/v4-shims.css b/deps/font-awesome-6.4.2/css/v4-shims.css
new file mode 100644
index 00000000..a85953d1
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/v4-shims.css
@@ -0,0 +1,2194 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa.fa-glass:before {
+  content: "\f000"; }
+
+.fa.fa-envelope-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-o:before {
+  content: "\f0e0"; }
+
+.fa.fa-star-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-o:before {
+  content: "\f005"; }
+
+.fa.fa-remove:before {
+  content: "\f00d"; }
+
+.fa.fa-close:before {
+  content: "\f00d"; }
+
+.fa.fa-gear:before {
+  content: "\f013"; }
+
+.fa.fa-trash-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-trash-o:before {
+  content: "\f2ed"; }
+
+.fa.fa-home:before {
+  content: "\f015"; }
+
+.fa.fa-file-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-file-o:before {
+  content: "\f15b"; }
+
+.fa.fa-clock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-clock-o:before {
+  content: "\f017"; }
+
+.fa.fa-arrow-circle-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-down:before {
+  content: "\f358"; }
+
+.fa.fa-arrow-circle-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-up:before {
+  content: "\f35b"; }
+
+.fa.fa-play-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-play-circle-o:before {
+  content: "\f144"; }
+
+.fa.fa-repeat:before {
+  content: "\f01e"; }
+
+.fa.fa-rotate-right:before {
+  content: "\f01e"; }
+
+.fa.fa-refresh:before {
+  content: "\f021"; }
+
+.fa.fa-list-alt {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-list-alt:before {
+  content: "\f022"; }
+
+.fa.fa-dedent:before {
+  content: "\f03b"; }
+
+.fa.fa-video-camera:before {
+  content: "\f03d"; }
+
+.fa.fa-picture-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-picture-o:before {
+  content: "\f03e"; }
+
+.fa.fa-photo {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-photo:before {
+  content: "\f03e"; }
+
+.fa.fa-image {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-image:before {
+  content: "\f03e"; }
+
+.fa.fa-map-marker:before {
+  content: "\f3c5"; }
+
+.fa.fa-pencil-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pencil-square-o:before {
+  content: "\f044"; }
+
+.fa.fa-edit {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-edit:before {
+  content: "\f044"; }
+
+.fa.fa-share-square-o:before {
+  content: "\f14d"; }
+
+.fa.fa-check-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-check-square-o:before {
+  content: "\f14a"; }
+
+.fa.fa-arrows:before {
+  content: "\f0b2"; }
+
+.fa.fa-times-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-circle-o:before {
+  content: "\f057"; }
+
+.fa.fa-check-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-check-circle-o:before {
+  content: "\f058"; }
+
+.fa.fa-mail-forward:before {
+  content: "\f064"; }
+
+.fa.fa-expand:before {
+  content: "\f424"; }
+
+.fa.fa-compress:before {
+  content: "\f422"; }
+
+.fa.fa-eye {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-eye-slash {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-warning:before {
+  content: "\f071"; }
+
+.fa.fa-calendar:before {
+  content: "\f073"; }
+
+.fa.fa-arrows-v:before {
+  content: "\f338"; }
+
+.fa.fa-arrows-h:before {
+  content: "\f337"; }
+
+.fa.fa-bar-chart:before {
+  content: "\e0e3"; }
+
+.fa.fa-bar-chart-o:before {
+  content: "\e0e3"; }
+
+.fa.fa-twitter-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-twitter-square:before {
+  content: "\f081"; }
+
+.fa.fa-facebook-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook-square:before {
+  content: "\f082"; }
+
+.fa.fa-gears:before {
+  content: "\f085"; }
+
+.fa.fa-thumbs-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-thumbs-o-up:before {
+  content: "\f164"; }
+
+.fa.fa-thumbs-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-thumbs-o-down:before {
+  content: "\f165"; }
+
+.fa.fa-heart-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-heart-o:before {
+  content: "\f004"; }
+
+.fa.fa-sign-out:before {
+  content: "\f2f5"; }
+
+.fa.fa-linkedin-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-linkedin-square:before {
+  content: "\f08c"; }
+
+.fa.fa-thumb-tack:before {
+  content: "\f08d"; }
+
+.fa.fa-external-link:before {
+  content: "\f35d"; }
+
+.fa.fa-sign-in:before {
+  content: "\f2f6"; }
+
+.fa.fa-github-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-github-square:before {
+  content: "\f092"; }
+
+.fa.fa-lemon-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-lemon-o:before {
+  content: "\f094"; }
+
+.fa.fa-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-square-o:before {
+  content: "\f0c8"; }
+
+.fa.fa-bookmark-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-bookmark-o:before {
+  content: "\f02e"; }
+
+.fa.fa-twitter {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook:before {
+  content: "\f39e"; }
+
+.fa.fa-facebook-f {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook-f:before {
+  content: "\f39e"; }
+
+.fa.fa-github {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-credit-card {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-feed:before {
+  content: "\f09e"; }
+
+.fa.fa-hdd-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hdd-o:before {
+  content: "\f0a0"; }
+
+.fa.fa-hand-o-right {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-right:before {
+  content: "\f0a4"; }
+
+.fa.fa-hand-o-left {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-left:before {
+  content: "\f0a5"; }
+
+.fa.fa-hand-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-up:before {
+  content: "\f0a6"; }
+
+.fa.fa-hand-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-down:before {
+  content: "\f0a7"; }
+
+.fa.fa-globe:before {
+  content: "\f57d"; }
+
+.fa.fa-tasks:before {
+  content: "\f828"; }
+
+.fa.fa-arrows-alt:before {
+  content: "\f31e"; }
+
+.fa.fa-group:before {
+  content: "\f0c0"; }
+
+.fa.fa-chain:before {
+  content: "\f0c1"; }
+
+.fa.fa-cut:before {
+  content: "\f0c4"; }
+
+.fa.fa-files-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-files-o:before {
+  content: "\f0c5"; }
+
+.fa.fa-floppy-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-floppy-o:before {
+  content: "\f0c7"; }
+
+.fa.fa-save {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-save:before {
+  content: "\f0c7"; }
+
+.fa.fa-navicon:before {
+  content: "\f0c9"; }
+
+.fa.fa-reorder:before {
+  content: "\f0c9"; }
+
+.fa.fa-magic:before {
+  content: "\e2ca"; }
+
+.fa.fa-pinterest {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pinterest-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pinterest-square:before {
+  content: "\f0d3"; }
+
+.fa.fa-google-plus-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-square:before {
+  content: "\f0d4"; }
+
+.fa.fa-google-plus {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus:before {
+  content: "\f0d5"; }
+
+.fa.fa-money:before {
+  content: "\f3d1"; }
+
+.fa.fa-unsorted:before {
+  content: "\f0dc"; }
+
+.fa.fa-sort-desc:before {
+  content: "\f0dd"; }
+
+.fa.fa-sort-asc:before {
+  content: "\f0de"; }
+
+.fa.fa-linkedin {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-linkedin:before {
+  content: "\f0e1"; }
+
+.fa.fa-rotate-left:before {
+  content: "\f0e2"; }
+
+.fa.fa-legal:before {
+  content: "\f0e3"; }
+
+.fa.fa-tachometer:before {
+  content: "\f625"; }
+
+.fa.fa-dashboard:before {
+  content: "\f625"; }
+
+.fa.fa-comment-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-comment-o:before {
+  content: "\f075"; }
+
+.fa.fa-comments-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-comments-o:before {
+  content: "\f086"; }
+
+.fa.fa-flash:before {
+  content: "\f0e7"; }
+
+.fa.fa-clipboard:before {
+  content: "\f0ea"; }
+
+.fa.fa-lightbulb-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-lightbulb-o:before {
+  content: "\f0eb"; }
+
+.fa.fa-exchange:before {
+  content: "\f362"; }
+
+.fa.fa-cloud-download:before {
+  content: "\f0ed"; }
+
+.fa.fa-cloud-upload:before {
+  content: "\f0ee"; }
+
+.fa.fa-bell-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-bell-o:before {
+  content: "\f0f3"; }
+
+.fa.fa-cutlery:before {
+  content: "\f2e7"; }
+
+.fa.fa-file-text-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-file-text-o:before {
+  content: "\f15c"; }
+
+.fa.fa-building-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-building-o:before {
+  content: "\f1ad"; }
+
+.fa.fa-hospital-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hospital-o:before {
+  content: "\f0f8"; }
+
+.fa.fa-tablet:before {
+  content: "\f3fa"; }
+
+.fa.fa-mobile:before {
+  content: "\f3cd"; }
+
+.fa.fa-mobile-phone:before {
+  content: "\f3cd"; }
+
+.fa.fa-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-circle-o:before {
+  content: "\f111"; }
+
+.fa.fa-mail-reply:before {
+  content: "\f3e5"; }
+
+.fa.fa-github-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-folder-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-folder-o:before {
+  content: "\f07b"; }
+
+.fa.fa-folder-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-folder-open-o:before {
+  content: "\f07c"; }
+
+.fa.fa-smile-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-smile-o:before {
+  content: "\f118"; }
+
+.fa.fa-frown-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-frown-o:before {
+  content: "\f119"; }
+
+.fa.fa-meh-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-meh-o:before {
+  content: "\f11a"; }
+
+.fa.fa-keyboard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-keyboard-o:before {
+  content: "\f11c"; }
+
+.fa.fa-flag-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-flag-o:before {
+  content: "\f024"; }
+
+.fa.fa-mail-reply-all:before {
+  content: "\f122"; }
+
+.fa.fa-star-half-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-half-o:before {
+  content: "\f5c0"; }
+
+.fa.fa-star-half-empty {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-half-empty:before {
+  content: "\f5c0"; }
+
+.fa.fa-star-half-full {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-half-full:before {
+  content: "\f5c0"; }
+
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+  content: "\f203"; }
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+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
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+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-cc {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-cc:before {
+  content: "\f20a"; }
+
+.fa.fa-ils:before {
+  content: "\f20b"; }
+
+.fa.fa-shekel:before {
+  content: "\f20b"; }
+
+.fa.fa-sheqel:before {
+  content: "\f20b"; }
+
+.fa.fa-buysellads {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-connectdevelop {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-dashcube {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-forumbee {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-leanpub {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-sellsy {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-shirtsinbulk {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-simplybuilt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-skyatlas {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-diamond {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-diamond:before {
+  content: "\f3a5"; }
+
+.fa.fa-transgender:before {
+  content: "\f224"; }
+
+.fa.fa-intersex:before {
+  content: "\f224"; }
+
+.fa.fa-transgender-alt:before {
+  content: "\f225"; }
+
+.fa.fa-facebook-official {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
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+  content: "\f09a"; }
+
+.fa.fa-pinterest-p {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-whatsapp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-hotel:before {
+  content: "\f236"; }
+
+.fa.fa-viacoin {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-medium {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-y-combinator {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yc {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yc:before {
+  content: "\f23b"; }
+
+.fa.fa-optin-monster {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-opencart {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-expeditedssl {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-battery-4:before {
+  content: "\f240"; }
+
+.fa.fa-battery:before {
+  content: "\f240"; }
+
+.fa.fa-battery-3:before {
+  content: "\f241"; }
+
+.fa.fa-battery-2:before {
+  content: "\f242"; }
+
+.fa.fa-battery-1:before {
+  content: "\f243"; }
+
+.fa.fa-battery-0:before {
+  content: "\f244"; }
+
+.fa.fa-object-group {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-object-ungroup {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-sticky-note-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-sticky-note-o:before {
+  content: "\f249"; }
+
+.fa.fa-cc-jcb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-cc-diners-club {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-clone {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hourglass-o:before {
+  content: "\f254"; }
+
+.fa.fa-hourglass-1:before {
+  content: "\f251"; }
+
+.fa.fa-hourglass-2:before {
+  content: "\f252"; }
+
+.fa.fa-hourglass-3:before {
+  content: "\f253"; }
+
+.fa.fa-hand-rock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-rock-o:before {
+  content: "\f255"; }
+
+.fa.fa-hand-grab-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-grab-o:before {
+  content: "\f255"; }
+
+.fa.fa-hand-paper-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-paper-o:before {
+  content: "\f256"; }
+
+.fa.fa-hand-stop-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-stop-o:before {
+  content: "\f256"; }
+
+.fa.fa-hand-scissors-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-scissors-o:before {
+  content: "\f257"; }
+
+.fa.fa-hand-lizard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-lizard-o:before {
+  content: "\f258"; }
+
+.fa.fa-hand-spock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-spock-o:before {
+  content: "\f259"; }
+
+.fa.fa-hand-pointer-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-pointer-o:before {
+  content: "\f25a"; }
+
+.fa.fa-hand-peace-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-peace-o:before {
+  content: "\f25b"; }
+
+.fa.fa-registered {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-creative-commons {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gg {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gg-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-odnoklassniki {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-odnoklassniki-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-odnoklassniki-square:before {
+  content: "\f264"; }
+
+.fa.fa-get-pocket {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wikipedia-w {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-safari {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-chrome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-firefox {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-opera {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-internet-explorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-television:before {
+  content: "\f26c"; }
+
+.fa.fa-contao {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-500px {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-amazon {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-calendar-plus-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-plus-o:before {
+  content: "\f271"; }
+
+.fa.fa-calendar-minus-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-minus-o:before {
+  content: "\f272"; }
+
+.fa.fa-calendar-times-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-times-o:before {
+  content: "\f273"; }
+
+.fa.fa-calendar-check-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-check-o:before {
+  content: "\f274"; }
+
+.fa.fa-map-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-map-o:before {
+  content: "\f279"; }
+
+.fa.fa-commenting:before {
+  content: "\f4ad"; }
+
+.fa.fa-commenting-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-commenting-o:before {
+  content: "\f4ad"; }
+
+.fa.fa-houzz {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-vimeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-vimeo:before {
+  content: "\f27d"; }
+
+.fa.fa-black-tie {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fonticons {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-reddit-alien {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-edge {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-credit-card-alt:before {
+  content: "\f09d"; }
+
+.fa.fa-codiepie {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-modx {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fort-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-usb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-product-hunt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-mixcloud {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-scribd {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o:before {
+  content: "\f28b"; }
+
+.fa.fa-stop-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-stop-circle-o:before {
+  content: "\f28d"; }
+
+.fa.fa-bluetooth {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-bluetooth-b {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gitlab {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpbeginner {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpforms {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-envira {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt:before {
+  content: "\f368"; }
+
+.fa.fa-question-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-question-circle-o:before {
+  content: "\f059"; }
+
+.fa.fa-volume-control-phone:before {
+  content: "\f2a0"; }
+
+.fa.fa-asl-interpreting:before {
+  content: "\f2a3"; }
+
+.fa.fa-deafness:before {
+  content: "\f2a4"; }
+
+.fa.fa-hard-of-hearing:before {
+  content: "\f2a4"; }
+
+.fa.fa-glide {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-glide-g {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-signing:before {
+  content: "\f2a7"; }
+
+.fa.fa-viadeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa.fa-snapchat {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa.fa-snapchat-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa.fa-pied-piper {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-first-order {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yoast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-themeisle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official:before {
+  content: "\f2b3"; }
+
+.fa.fa-google-plus-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-circle:before {
+  content: "\f2b3"; }
+
+.fa.fa-font-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa:before {
+  content: "\f2b4"; }
+
+.fa.fa-handshake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-handshake-o:before {
+  content: "\f2b5"; }
+
+.fa.fa-envelope-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-open-o:before {
+  content: "\f2b6"; }
+
+.fa.fa-linode {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-address-book-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-book-o:before {
+  content: "\f2b9"; }
+
+.fa.fa-vcard:before {
+  content: "\f2bb"; }
+
+.fa.fa-address-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-card-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-vcard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-vcard-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-user-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-circle-o:before {
+  content: "\f2bd"; }
+
+.fa.fa-user-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-o:before {
+  content: "\f007"; }
+
+.fa.fa-id-badge {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license:before {
+  content: "\f2c2"; }
+
+.fa.fa-id-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-id-card-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-drivers-license-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-quora {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-free-code-camp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-telegram {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-thermometer-4:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer-3:before {
+  content: "\f2c8"; }
+
+.fa.fa-thermometer-2:before {
+  content: "\f2c9"; }
+
+.fa.fa-thermometer-1:before {
+  content: "\f2ca"; }
+
+.fa.fa-thermometer-0:before {
+  content: "\f2cb"; }
+
+.fa.fa-bathtub:before {
+  content: "\f2cd"; }
+
+.fa.fa-s15:before {
+  content: "\f2cd"; }
+
+.fa.fa-window-maximize {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-restore {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle:before {
+  content: "\f410"; }
+
+.fa.fa-window-close-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-close-o:before {
+  content: "\f410"; }
+
+.fa.fa-times-rectangle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle-o:before {
+  content: "\f410"; }
+
+.fa.fa-bandcamp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-grav {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-etsy {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-imdb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-ravelry {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast:before {
+  content: "\f2da"; }
+
+.fa.fa-snowflake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-snowflake-o:before {
+  content: "\f2dc"; }
+
+.fa.fa-superpowers {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpexplorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-meetup {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
diff --git a/deps/font-awesome-6.4.2/css/v4-shims.min.css b/deps/font-awesome-6.4.2/css/v4-shims.min.css
new file mode 100644
index 00000000..64e4e8d8
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/v4-shims.min.css
@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
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diff --git a/deps/headroom-0.11.0/headroom.min.js b/deps/headroom-0.11.0/headroom.min.js
new file mode 100644
index 00000000..433069fd
--- /dev/null
+++ b/deps/headroom-0.11.0/headroom.min.js
@@ -0,0 +1,7 @@
+/*!
+ * headroom.js v0.11.0 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2020 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?module.exports=n():"function"==typeof define&&define.amd?define(n):(t=t||self).Headroom=n()}(this,function(){"use strict";function t(){return"undefined"!=typeof window}function d(t){return function(t){return t&&t.document&&function(t){return 9===t.nodeType}(t.document)}(t)?function(t){var n=t.document,o=n.body,s=n.documentElement;return{scrollHeight:function(){return Math.max(o.scrollHeight,s.scrollHeight,o.offsetHeight,s.offsetHeight,o.clientHeight,s.clientHeight)},height:function(){return t.innerHeight||s.clientHeight||o.clientHeight},scrollY:function(){return void 0!==t.pageYOffset?t.pageYOffset:(s||o.parentNode||o).scrollTop}}}(t):function(t){return{scrollHeight:function(){return Math.max(t.scrollHeight,t.offsetHeight,t.clientHeight)},height:function(){return Math.max(t.offsetHeight,t.clientHeight)},scrollY:function(){return t.scrollTop}}}(t)}function n(t,s,e){var n,o=function(){var n=!1;try{var t={get passive(){n=!0}};window.addEventListener("test",t,t),window.removeEventListener("test",t,t)}catch(t){n=!1}return n}(),i=!1,r=d(t),l=r.scrollY(),a={};function c(){var t=Math.round(r.scrollY()),n=r.height(),o=r.scrollHeight();a.scrollY=t,a.lastScrollY=l,a.direction=l<t?"down":"up",a.distance=Math.abs(t-l),a.isOutOfBounds=t<0||o<t+n,a.top=t<=s.offset,a.bottom=o<=t+n,a.toleranceExceeded=a.distance>s.tolerance[a.direction],e(a),l=t,i=!1}function h(){i||(i=!0,n=requestAnimationFrame(c))}var u=!!o&&{passive:!0,capture:!1};return t.addEventListener("scroll",h,u),c(),{destroy:function(){cancelAnimationFrame(n),t.removeEventListener("scroll",h,u)}}}function o(t,n){n=n||{},Object.assign(this,o.options,n),this.classes=Object.assign({},o.options.classes,n.classes),this.elem=t,this.tolerance=function(t){return t===Object(t)?t:{down:t,up:t}}(this.tolerance),this.initialised=!1,this.frozen=!1}return o.prototype={constructor:o,init:function(){return o.cutsTheMustard&&!this.initialised&&(this.addClass("initial"),this.initialised=!0,setTimeout(function(t){t.scrollTracker=n(t.scroller,{offset:t.offset,tolerance:t.tolerance},t.update.bind(t))},100,this)),this},destroy:function(){this.initialised=!1,Object.keys(this.classes).forEach(this.removeClass,this),this.scrollTracker.destroy()},unpin:function(){!this.hasClass("pinned")&&this.hasClass("unpinned")||(this.addClass("unpinned"),this.removeClass("pinned"),this.onUnpin&&this.onUnpin.call(this))},pin:function(){this.hasClass("unpinned")&&(this.addClass("pinned"),this.removeClass("unpinned"),this.onPin&&this.onPin.call(this))},freeze:function(){this.frozen=!0,this.addClass("frozen")},unfreeze:function(){this.frozen=!1,this.removeClass("frozen")},top:function(){this.hasClass("top")||(this.addClass("top"),this.removeClass("notTop"),this.onTop&&this.onTop.call(this))},notTop:function(){this.hasClass("notTop")||(this.addClass("notTop"),this.removeClass("top"),this.onNotTop&&this.onNotTop.call(this))},bottom:function(){this.hasClass("bottom")||(this.addClass("bottom"),this.removeClass("notBottom"),this.onBottom&&this.onBottom.call(this))},notBottom:function(){this.hasClass("notBottom")||(this.addClass("notBottom"),this.removeClass("bottom"),this.onNotBottom&&this.onNotBottom.call(this))},shouldUnpin:function(t){return"down"===t.direction&&!t.top&&t.toleranceExceeded},shouldPin:function(t){return"up"===t.direction&&t.toleranceExceeded||t.top},addClass:function(t){this.elem.classList.add.apply(this.elem.classList,this.classes[t].split(" "))},removeClass:function(t){this.elem.classList.remove.apply(this.elem.classList,this.classes[t].split(" "))},hasClass:function(t){return this.classes[t].split(" ").every(function(t){return this.classList.contains(t)},this.elem)},update:function(t){t.isOutOfBounds||!0!==this.frozen&&(t.top?this.top():this.notTop(),t.bottom?this.bottom():this.notBottom(),this.shouldUnpin(t)?this.unpin():this.shouldPin(t)&&this.pin())}},o.options={tolerance:{up:0,down:0},offset:0,scroller:t()?window:null,classes:{frozen:"headroom--frozen",pinned:"headroom--pinned",unpinned:"headroom--unpinned",top:"headroom--top",notTop:"headroom--not-top",bottom:"headroom--bottom",notBottom:"headroom--not-bottom",initial:"headroom"}},o.cutsTheMustard=!!(t()&&function(){}.bind&&"classList"in document.documentElement&&Object.assign&&Object.keys&&requestAnimationFrame),o});
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diff --git a/deps/headroom-0.11.0/jQuery.headroom.min.js b/deps/headroom-0.11.0/jQuery.headroom.min.js
new file mode 100644
index 00000000..17f70c9e
--- /dev/null
+++ b/deps/headroom-0.11.0/jQuery.headroom.min.js
@@ -0,0 +1,7 @@
+/*!
+ * headroom.js v0.9.4 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2017 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(a){a&&(a.fn.headroom=function(b){return this.each(function(){var c=a(this),d=c.data("headroom"),e="object"==typeof b&&b;e=a.extend(!0,{},Headroom.options,e),d||(d=new Headroom(this,e),d.init(),c.data("headroom",d)),"string"==typeof b&&(d[b](),"destroy"===b&&c.removeData("headroom"))})},a("[data-headroom]").each(function(){var b=a(this);b.headroom(b.data())}))}(window.Zepto||window.jQuery);
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diff --git a/deps/search-1.0.0/autocomplete.jquery.min.js b/deps/search-1.0.0/autocomplete.jquery.min.js
new file mode 100644
index 00000000..fb63a6a2
--- /dev/null
+++ b/deps/search-1.0.0/autocomplete.jquery.min.js
@@ -0,0 +1,7 @@
+/*!
+ * autocomplete.js 0.38.0
+ * https://github.com/algolia/autocomplete.js
+ * Copyright 2020 Algolia, Inc. and other contributors; Licensed MIT
+ */
+!function(a){function b(d){if(c[d])return c[d].exports;var e=c[d]={exports:{},id:d,loaded:!1};return a[d].call(e.exports,e,e.exports,b),e.loaded=!0,e.exports}var c={};b.m=a,b.c=c,b.p="",b(0)}([function(a,b,c){"use strict";a.exports=c(1)},function(a,b,c){"use strict";var d=c(2),e=c(3);d.element=e;var f=c(4);f.isArray=e.isArray,f.isFunction=e.isFunction,f.isObject=e.isPlainObject,f.bind=e.proxy,f.each=function(a,b){function c(a,c){return b(c,a)}e.each(a,c)},f.map=e.map,f.mixin=e.extend,f.Event=e.Event;var g,h,i,j=c(5),k=c(6);g=e.fn.autocomplete,h="aaAutocomplete",i={initialize:function(a,b){function c(){var c,d=e(this),f=new k({el:d});c=new j({input:d,eventBus:f,dropdownMenuContainer:a.dropdownMenuContainer,hint:void 0===a.hint||!!a.hint,minLength:a.minLength,autoselect:a.autoselect,autoselectOnBlur:a.autoselectOnBlur,tabAutocomplete:a.tabAutocomplete,openOnFocus:a.openOnFocus,templates:a.templates,debug:a.debug,clearOnSelected:a.clearOnSelected,cssClasses:a.cssClasses,datasets:b,keyboardShortcuts:a.keyboardShortcuts,appendTo:a.appendTo,autoWidth:a.autoWidth}),d.data(h,c)}return b=f.isArray(b)?b:[].slice.call(arguments,1),a=a||{},this.each(c)},open:function(){function a(){var a,b=e(this);(a=b.data(h))&&a.open()}return this.each(a)},close:function(){function a(){var a,b=e(this);(a=b.data(h))&&a.close()}return this.each(a)},val:function(a){function b(){var b,c=e(this);(b=c.data(h))&&b.setVal(a)}return arguments.length?this.each(b):function(a){var b,c;return(b=a.data(h))&&(c=b.getVal()),c}(this.first())},destroy:function(){function a(){var a,b=e(this);(a=b.data(h))&&(a.destroy(),b.removeData(h))}return this.each(a)}},e.fn.autocomplete=function(a){var b;return 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f=document.createElement("div");f.appendChild(document.createTextNode(c));var g=document.createElement("div");return g.appendChild(document.createTextNode(a)),g.innerHTML.replace(RegExp(d(e.innerHTML),"g"),b).replace(RegExp(d(f.innerHTML),"g"),c)}}},function(a,b,c){"use strict";function d(a){var b,c;if(a=a||{},a.input||i.error("missing input"),this.isActivated=!1,this.debug=!!a.debug,this.autoselect=!!a.autoselect,this.autoselectOnBlur=!!a.autoselectOnBlur,this.openOnFocus=!!a.openOnFocus,this.minLength=i.isNumber(a.minLength)?a.minLength:1,this.autoWidth=void 0===a.autoWidth||!!a.autoWidth,this.clearOnSelected=!!a.clearOnSelected,this.tabAutocomplete=void 0===a.tabAutocomplete||!!a.tabAutocomplete,a.hint=!!a.hint,a.hint&&a.appendTo)throw new Error("[autocomplete.js] hint and appendTo options can't be used at the same time");this.css=a.css=i.mixin({},o,a.appendTo?o.appendTo:{}),this.cssClasses=a.cssClasses=i.mixin({},o.defaultClasses,a.cssClasses||{}),this.cssClasses.prefix=a.cssClasses.formattedPrefix=i.formatPrefix(this.cssClasses.prefix,this.cssClasses.noPrefix),this.listboxId=a.listboxId=[this.cssClasses.root,"listbox",i.getUniqueId()].join("-");var f=e(a);this.$node=f.wrapper;var g=this.$input=f.input;b=f.menu,c=f.hint,a.dropdownMenuContainer&&j.element(a.dropdownMenuContainer).css("position","relative").append(b.css("top","0")),g.on("blur.aa",function(a){var c=document.activeElement;i.isMsie()&&(b[0]===c||b[0].contains(c))&&(a.preventDefault(),a.stopImmediatePropagation(),i.defer(function(){g.focus()}))}),b.on("mousedown.aa",function(a){a.preventDefault()}),this.eventBus=a.eventBus||new k({el:g}),this.dropdown=new d.Dropdown({appendTo:a.appendTo,wrapper:this.$node,menu:b,datasets:a.datasets,templates:a.templates,cssClasses:a.cssClasses,minLength:this.minLength}).onSync("suggestionClicked",this._onSuggestionClicked,this).onSync("cursorMoved",this._onCursorMoved,this).onSync("cursorRemoved",this._onCursorRemoved,this).onSync("opened",this._onOpened,this).onSync("closed",this._onClosed,this).onSync("shown",this._onShown,this).onSync("empty",this._onEmpty,this).onSync("redrawn",this._onRedrawn,this).onAsync("datasetRendered",this._onDatasetRendered,this),this.input=new 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g=n.dropdown.replace("%PREFIX%",a.cssClasses.prefix).replace("%DROPDOWN_MENU%",a.cssClasses.dropdownMenu);d=j.element(g).css(a.css.dropdown).attr({role:"listbox",id:a.listboxId}),a.templates&&a.templates.dropdownMenu&&d.html(i.templatify(a.templates.dropdownMenu)()),e=b.clone().css(a.css.hint).css(f(b)),e.val("").addClass(i.className(a.cssClasses.prefix,a.cssClasses.hint,!0)).removeAttr("id name placeholder required").prop("readonly",!0).attr({"aria-hidden":"true",autocomplete:"off",spellcheck:"false",tabindex:-1}),e.removeData&&e.removeData(),b.data(h,{"aria-autocomplete":b.attr("aria-autocomplete"),"aria-expanded":b.attr("aria-expanded"),"aria-owns":b.attr("aria-owns"),autocomplete:b.attr("autocomplete"),dir:b.attr("dir"),role:b.attr("role"),spellcheck:b.attr("spellcheck"),style:b.attr("style"),type:b.attr("type")}),b.addClass(i.className(a.cssClasses.prefix,a.cssClasses.input,!0)).attr({autocomplete:"off",spellcheck:!1,role:"combobox","aria-autocomplete":a.datasets&&a.datasets[0]&&a.datasets[0].displayKey?"both":"list","aria-expanded":"false","aria-label":a.ariaLabel,"aria-owns":a.listboxId}).css(a.hint?a.css.input:a.css.inputWithNoHint);try{b.attr("dir")||b.attr("dir","auto")}catch(a){}return c=a.appendTo?c.appendTo(j.element(a.appendTo).eq(0)).eq(0):b.wrap(c).parent(),c.prepend(a.hint?e:null).append(d),{wrapper:c,input:b,hint:e,menu:d}}function f(a){return{backgroundAttachment:a.css("background-attachment"),backgroundClip:a.css("background-clip"),backgroundColor:a.css("background-color"),backgroundImage:a.css("background-image"),backgroundOrigin:a.css("background-origin"),backgroundPosition:a.css("background-position"),backgroundRepeat:a.css("background-repeat"),backgroundSize:a.css("background-size")}}function g(a,b){var c=a.find(i.className(b.prefix,b.input));i.each(c.data(h),function(a,b){void 0===a?c.removeAttr(b):c.attr(b,a)}),c.detach().removeClass(i.className(b.prefix,b.input,!0)).insertAfter(a),c.removeData&&c.removeData(h),a.remove()}var h="aaAttrs",i=c(4),j=c(2),k=c(6),l=c(7),m=c(16),n=c(18),o=c(19);i.mixin(d.prototype,{_bindKeyboardShortcuts:function(a){if(a.keyboardShortcuts){var b=this.$input,c=[];i.each(a.keyboardShortcuts,function(a){"string"==typeof a&&(a=a.toUpperCase().charCodeAt(0)),c.push(a)}),j.element(document).keydown(function(a){var d=a.target||a.srcElement,e=d.tagName;if(!d.isContentEditable&&"INPUT"!==e&&"SELECT"!==e&&"TEXTAREA"!==e){var f=a.which||a.keyCode;c.indexOf(f)!==-1&&(b.focus(),a.stopPropagation(),a.preventDefault())}})}},_onSuggestionClicked:function(a,b){var c,d={selectionMethod:"click"};(c=this.dropdown.getDatumForSuggestion(b))&&this._select(c,d)},_onCursorMoved:function(a,b){var c=this.dropdown.getDatumForCursor(),d=this.dropdown.getCurrentCursor().attr("id");this.input.setActiveDescendant(d),c&&(b&&this.input.setInputValue(c.value,!0),this.eventBus.trigger("cursorchanged",c.raw,c.datasetName))},_onCursorRemoved:function(){this.input.resetInputValue(),this._updateHint(),this.eventBus.trigger("cursorremoved")},_onDatasetRendered:function(){this._updateHint(),this.eventBus.trigger("updated")},_onOpened:function(){this._updateHint(),this.input.expand(),this.eventBus.trigger("opened")},_onEmpty:function(){this.eventBus.trigger("empty")},_onRedrawn:function(){this.$node.css("top","0px"),this.$node.css("left","0px");var a=this.$input[0].getBoundingClientRect();this.autoWidth&&this.$node.css("width",a.width+"px");var b=this.$node[0].getBoundingClientRect(),c=a.bottom-b.top;this.$node.css("top",c+"px");var d=a.left-b.left;this.$node.css("left",d+"px"),this.eventBus.trigger("redrawn")},_onShown:function(){this.eventBus.trigger("shown"),this.autoselect&&this.dropdown.cursorTopSuggestion()},_onClosed:function(){this.input.clearHint(),this.input.removeActiveDescendant(),this.input.collapse(),this.eventBus.trigger("closed")},_onFocused:function(){if(this.isActivated=!0,this.openOnFocus){var a=this.input.getQuery();a.length>=this.minLength?this.dropdown.update(a):this.dropdown.empty(),this.dropdown.open()}},_onBlurred:function(){var a,b;a=this.dropdown.getDatumForCursor(),b=this.dropdown.getDatumForTopSuggestion();var c={selectionMethod:"blur"};this.debug||(this.autoselectOnBlur&&a?this._select(a,c):this.autoselectOnBlur&&b?this._select(b,c):(this.isActivated=!1,this.dropdown.empty(),this.dropdown.close()))},_onEnterKeyed:function(a,b){var c,d;c=this.dropdown.getDatumForCursor(),d=this.dropdown.getDatumForTopSuggestion();var e={selectionMethod:"enterKey"};c?(this._select(c,e),b.preventDefault()):this.autoselect&&d&&(this._select(d,e),b.preventDefault())},_onTabKeyed:function(a,b){if(!this.tabAutocomplete)return void this.dropdown.close();var c,d={selectionMethod:"tabKey"};(c=this.dropdown.getDatumForCursor())?(this._select(c,d),b.preventDefault()):this._autocomplete(!0)},_onEscKeyed:function(){this.dropdown.close(),this.input.resetInputValue()},_onUpKeyed:function(){var a=this.input.getQuery();this.dropdown.isEmpty&&a.length>=this.minLength?this.dropdown.update(a):this.dropdown.moveCursorUp(),this.dropdown.open()},_onDownKeyed:function(){var a=this.input.getQuery();this.dropdown.isEmpty&&a.length>=this.minLength?this.dropdown.update(a):this.dropdown.moveCursorDown(),this.dropdown.open()},_onLeftKeyed:function(){"rtl"===this.dir&&this._autocomplete()},_onRightKeyed:function(){"ltr"===this.dir&&this._autocomplete()},_onQueryChanged:function(a,b){this.input.clearHintIfInvalid(),b.length>=this.minLength?this.dropdown.update(b):this.dropdown.empty(),this.dropdown.open(),this._setLanguageDirection()},_onWhitespaceChanged:function(){this._updateHint(),this.dropdown.open()},_setLanguageDirection:function(){var a=this.input.getLanguageDirection();this.dir!==a&&(this.dir=a,this.$node.css("direction",a),this.dropdown.setLanguageDirection(a))},_updateHint:function(){var a,b,c,d,e,f;a=this.dropdown.getDatumForTopSuggestion(),a&&this.dropdown.isVisible()&&!this.input.hasOverflow()?(b=this.input.getInputValue(),c=l.normalizeQuery(b),d=i.escapeRegExChars(c),e=new 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a=this.input.getInputValue();a.length>=this.minLength?this.dropdown.update(a):this.dropdown.empty()}this.dropdown.open()},close:function(){this.dropdown.close()},setVal:function(a){a=i.toStr(a),this.isActivated?this.input.setInputValue(a):(this.input.setQuery(a),this.input.setInputValue(a,!0)),this._setLanguageDirection()},getVal:function(){return this.input.getQuery()},destroy:function(){this.input.destroy(),this.dropdown.destroy(),g(this.$node,this.cssClasses),this.$node=null},getWrapper:function(){return this.dropdown.$container[0]}}),d.Dropdown=m,d.Input=l,d.sources=c(20),a.exports=d},function(a,b,c){"use strict";function d(a){a&&a.el||e.error("EventBus initialized without el"),this.$el=f.element(a.el)}var e=c(4),f=c(2);e.mixin(d.prototype,{trigger:function(a,b,c,d){var f=e.Event("autocomplete:"+a);return this.$el.trigger(f,[b,c,d]),f}}),a.exports=d},function(a,b,c){"use strict";function d(a){var b,c,d,f,g=this;a=a||{},a.input||i.error("input is 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b=h[a.which||a.keyCode];this._managePreventDefault(b,a),b&&this._shouldTrigger(b,a)&&this.trigger(b+"Keyed",a)},_onInput:function(){this._checkInputValue()},_managePreventDefault:function(a,b){var c,d,e;switch(a){case"tab":d=this.getHint(),e=this.getInputValue(),c=d&&d!==e&&!g(b);break;case"up":case"down":c=!g(b);break;default:c=!1}c&&b.preventDefault()},_shouldTrigger:function(a,b){var c;switch(a){case"tab":c=!g(b);break;default:c=!0}return c},_checkInputValue:function(){var a,b,c;a=this.getInputValue(),b=f(a,this.query),c=!(!b||!this.query)&&this.query.length!==a.length,this.query=a,b?c&&this.trigger("whitespaceChanged",this.query):this.trigger("queryChanged",this.query)},focus:function(){this.$input.focus()},blur:function(){this.$input.blur()},getQuery:function(){return this.query},setQuery:function(a){this.query=a},getInputValue:function(){return this.$input.val()},setInputValue:function(a,b){void 0===a&&(a=this.query),this.$input.val(a),b?this.clearHint():this._checkInputValue()},expand:function(){this.$input.attr("aria-expanded","true")},collapse:function(){this.$input.attr("aria-expanded","false")},setActiveDescendant:function(a){this.$input.attr("aria-activedescendant",a)},removeActiveDescendant:function(){this.$input.removeAttr("aria-activedescendant")},resetInputValue:function(){this.setInputValue(this.query,!0)},getHint:function(){return this.$hint.val()},setHint:function(a){this.$hint.val(a)},clearHint:function(){this.setHint("")},clearHintIfInvalid:function(){var a,b,c,d;a=this.getInputValue(),b=this.getHint(),c=a!==b&&0===b.indexOf(a),(d=""!==a&&c&&!this.hasOverflow())||this.clearHint()},getLanguageDirection:function(){return(this.$input.css("direction")||"ltr").toLowerCase()},hasOverflow:function(){var a=this.$input.width()-2;return this.$overflowHelper.text(this.getInputValue()),this.$overflowHelper.width()>=a},isCursorAtEnd:function(){var a,b,c;return 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+var c=[].slice.call(arguments,1);this.cacheSuggestions(a,b,c),this._render.apply(this,[a,b].concat(c))}}if(this.query=a,this.canceled=!1,this.shouldFetchFromCache(a))b.apply(this,[this.cachedSuggestions].concat(this.cachedRenderExtraArgs));else{var c=this,d=function(){c.canceled||c.source(a,b.bind(c))};if(this.debounce){var e=function(){c.debounceTimeout=null,d()};clearTimeout(this.debounceTimeout),this.debounceTimeout=setTimeout(e,this.debounce)}else d()}},cacheSuggestions:function(a,b,c){this.cachedQuery=a,this.cachedSuggestions=b,this.cachedRenderExtraArgs=c},shouldFetchFromCache:function(a){return this.cache&&this.cachedQuery===a&&this.cachedSuggestions&&this.cachedSuggestions.length},clearCachedSuggestions:function(){delete this.cachedQuery,delete this.cachedSuggestions,delete this.cachedRenderExtraArgs},cancel:function(){this.canceled=!0},clear:function(){this.$el&&(this.cancel(),this.$el.empty(),this.trigger("rendered",""))},isEmpty:function(){return this._isEmpty},destroy:function(){this.clearCachedSuggestions(),this.$el=null}}),a.exports=d},function(a,b){"use strict";a.exports={wrapper:'<span class="%ROOT%"></span>',dropdown:'<span class="%PREFIX%%DROPDOWN_MENU%"></span>',dataset:'<div class="%PREFIX%%DATASET%-%CLASS%"></div>',suggestions:'<span class="%PREFIX%%SUGGESTIONS%"></span>',suggestion:'<div class="%PREFIX%%SUGGESTION%"></div>'}},function(a,b,c){"use strict";var d=c(4),e={wrapper:{position:"relative",display:"inline-block"},hint:{position:"absolute",top:"0",left:"0",borderColor:"transparent",boxShadow:"none",opacity:"1"},input:{position:"relative",verticalAlign:"top",backgroundColor:"transparent"},inputWithNoHint:{position:"relative",verticalAlign:"top"},dropdown:{position:"absolute",top:"100%",left:"0",zIndex:"100",display:"none"},suggestions:{display:"block"},suggestion:{whiteSpace:"nowrap",cursor:"pointer"},suggestionChild:{whiteSpace:"normal"},ltr:{left:"0",right:"auto"},rtl:{left:"auto",right:"0"},defaultClasses:{root:"algolia-autocomplete",prefix:"aa",noPrefix:!1,dropdownMenu:"dropdown-menu",input:"input",hint:"hint",suggestions:"suggestions",suggestion:"suggestion",cursor:"cursor",dataset:"dataset",empty:"empty"},appendTo:{wrapper:{position:"absolute",zIndex:"100",display:"none"},input:{},inputWithNoHint:{},dropdown:{display:"block"}}};d.isMsie()&&d.mixin(e.input,{backgroundImage:"url(data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)"}),d.isMsie()&&d.isMsie()<=7&&d.mixin(e.input,{marginTop:"-1px"}),a.exports=e},function(a,b,c){"use strict";a.exports={hits:c(21),popularIn:c(24)}},function(a,b,c){"use strict";var d=c(4),e=c(22),f=c(23),g=function(){function a(a,d){return window.Promise.resolve().then(function(){return b.length&&(e=a.search(b),b=[]),e}).then(function(a){if(a)return c=a.results,c[d]})}var b=[],c=[],e=window.Promise.resolve();return function(c,e){return function(f,g){a(c.as,b.push({indexName:c.indexName,query:f,params:e})-1).then(function(a){a&&g(a.hits,a)}).catch(function(a){d.error(a.message)})}}}();a.exports=function(a,b){var c=f(a.as._ua);if(c&&c[0]>=3&&c[1]>20){var d="autocomplete.js "+e;a.as._ua.indexOf(d)===-1&&(a.as._ua+="; "+d)}return g(a,b)}},function(a,b){a.exports="0.38.0"},function(a,b){"use strict";a.exports=function(a){var b=a.match(/Algolia for JavaScript \((\d+\.)(\d+\.)(\d+)\)/)||a.match(/Algolia for vanilla JavaScript (\d+\.)(\d+\.)(\d+)/);if(b)return[b[1],b[2],b[3]]}},function(a,b,c){"use strict";var d=c(4),e=c(22),f=c(23);a.exports=function(a,b,c,g){function h(h,i){a.search(h,b,function(a,h){if(a)return void d.error(a.message);if(h.hits.length>0){var l=h.hits[0],m=d.mixin({hitsPerPage:0},c);delete m.source,delete m.index;var n=f(k.as._ua);return n&&n[0]>=3&&n[1]>20&&(b.additionalUA="autocomplete.js "+e),void k.search(j(l),m,function(a,b){if(a)return void d.error(a.message);var c=[];if(g.includeAll){var e=g.allTitle||"All departments";c.push(d.mixin({facet:{value:e,count:b.nbHits}},d.cloneDeep(l)))}d.each(b.facets,function(a,b){d.each(a,function(a,e){c.push(d.mixin({facet:{facet:b,value:e,count:a}},d.cloneDeep(l)))})});for(var f=1;f<h.hits.length;++f)c.push(h.hits[f]);i(c,h)})}i([])})}var i=f(a.as._ua);if(i&&i[0]>=3&&i[1]>20&&(b=b||{},b.additionalUA="autocomplete.js "+e),!c.source)return d.error("Missing 'source' key");var j=d.isFunction(c.source)?c.source:function(a){return a[c.source]};if(!c.index)return d.error("Missing 'index' key");var k=c.index;return g=g||{},h}}]);
\ No newline at end of file
diff --git a/deps/search-1.0.0/fuse.min.js b/deps/search-1.0.0/fuse.min.js
new file mode 100644
index 00000000..7def5985
--- /dev/null
+++ b/deps/search-1.0.0/fuse.min.js
@@ -0,0 +1,9 @@
+/**
+ * Fuse.js v6.4.6 - Lightweight fuzzy-search (http://fusejs.io)
+ *
+ * Copyright (c) 2021 Kiro Risk (http://kiro.me)
+ * All Rights Reserved. Apache Software License 2.0
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ */
+var e,t;e=this,t=function(){"use strict";function e(t){return(e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e})(t)}function t(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function n(e,t){for(var n=0;n<t.length;n++){var r=t[n];r.enumerable=r.enumerable||!1,r.configurable=!0,"value"in r&&(r.writable=!0),Object.defineProperty(e,r.key,r)}}function r(e,t,r){return t&&n(e.prototype,t),r&&n(e,r),e}function i(e,t,n){return t in e?Object.defineProperty(e,t,{value:n,enumerable:!0,configurable:!0,writable:!0}):e[t]=n,e}function o(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var r=Object.getOwnPropertySymbols(e);t&&(r=r.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,r)}return n}function c(e){for(var t=1;t<arguments.length;t++){var 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c=t.searchIn(n),a=c.isMatch,s=c.score,u=c.indices;a&&r.push({item:n,idx:i,matches:[{score:s,value:n,norm:o,indices:u}]})}})),r}},{key:"_searchLogical",value:function(e){var t=this,n=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},r=n.auto,i=void 0===r||r,o=function e(n){var r=Object.keys(n),o=ae(n);if(!o&&r.length>1&&!ce(n))return e(ue(n));if(se(n)){var c=o?n[ie]:r[0],a=o?n[oe]:n[c];if(!g(a))throw new Error(x(c));var s={keyId:j(c),pattern:a};return i&&(s.searcher=te(a,t)),s}var u={children:[],operator:r[0]};return r.forEach((function(t){var r=n[t];v(r)&&r.forEach((function(t){u.children.push(e(t))}))})),u};return ce(e)||(e=ue(e)),o(e)}(e,this.options),r=this._myIndex.records,i={},o=[];return r.forEach((function(e){var r=e.$,c=e.i;if(k(r)){var a=function e(n,r,i){if(!n.children){var o=n.keyId,c=n.searcher,a=t._findMatches({key:t._keyStore.get(o),value:t._myIndex.getValueForItemAtKeyId(r,o),searcher:c});return a&&a.length?[{idx:i,item:r,matches:a}]:[]}switch(n.operator){case ne:for(var s=[],u=0,h=n.children.length;u<h;u+=1){var f=e(n.children[u],r,i);if(!f.length)return[];s.push.apply(s,l(f))}return s;case re:for(var d=[],v=0,g=n.children.length;v<g;v+=1){var y=e(n.children[v],r,i);if(y.length){d.push.apply(d,l(y));break}}return d}}(n,r,c);a.length&&(i[c]||(i[c]={idx:c,item:r,matches:[]},o.push(i[c])),a.forEach((function(e){var t,n=e.matches;(t=i[c].matches).push.apply(t,l(n))})))}})),o}},{key:"_searchObjectList",value:function(e){var t=this,n=te(e,this.options),r=this._myIndex,i=r.keys,o=r.records,c=[];return o.forEach((function(e){var r=e.$,o=e.i;if(k(r)){var a=[];i.forEach((function(e,i){a.push.apply(a,l(t._findMatches({key:e,value:r[i],searcher:n})))})),a.length&&c.push({idx:o,item:r,matches:a})}})),c}},{key:"_findMatches",value:function(e){var t=e.key,n=e.value,r=e.searcher;if(!k(n))return[];var i=[];if(v(n))n.forEach((function(e){var n=e.v,o=e.i,c=e.n;if(k(n)){var a=r.searchIn(n),s=a.isMatch,u=a.score,h=a.indices;s&&i.push({score:u,key:t,value:n,idx:o,norm:c,indices:h})}}));else{var o=n.v,c=n.n,a=r.searchIn(o),s=a.isMatch,u=a.score,h=a.indices;s&&i.push({score:u,key:t,value:o,norm:c,indices:h})}return i}}]),e}();return ve.version="6.4.6",ve.createIndex=$,ve.parseIndex=function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},n=t.getFn,r=void 0===n?A.getFn:n,i=e.keys,o=e.records,c=new E({getFn:r});return c.setKeys(i),c.setIndexRecords(o),c},ve.config=A,function(){ee.push.apply(ee,arguments)}(Z),ve},"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):(e=e||self).Fuse=t();
\ No newline at end of file
diff --git a/deps/search-1.0.0/mark.min.js b/deps/search-1.0.0/mark.min.js
new file mode 100644
index 00000000..1eea0533
--- /dev/null
+++ b/deps/search-1.0.0/mark.min.js
@@ -0,0 +1,7 @@
+/*!***************************************************
+* mark.js v8.11.1
+* https://markjs.io/
+* Copyright (c) 2014–2018, Julian Kühnel
+* Released under the MIT license https://git.io/vwTVl
+*****************************************************/
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):e.Mark=t()}(this,function(){"use strict";var e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e},t=function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")},n=function(){function e(e,t){for(var n=0;n<t.length;n++){var r=t[n];r.enumerable=r.enumerable||!1,r.configurable=!0,"value"in r&&(r.writable=!0),Object.defineProperty(e,r.key,r)}}return function(t,n,r){return n&&e(t.prototype,n),r&&e(t,r),t}}(),r=Object.assign||function(e){for(var t=1;t<arguments.length;t++){var n=arguments[t];for(var r in n)Object.prototype.hasOwnProperty.call(n,r)&&(e[r]=n[r])}return e},i=function(){function e(n){var r=!(arguments.length>1&&void 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t=e.getAttribute("src").trim();return"about:blank"===e.contentWindow.location.href&&"about:blank"!==t&&t}},{key:"observeIframeLoad",value:function(e,t,n){var r=this,i=!1,o=null,a=function a(){if(!i){i=!0,clearTimeout(o);try{r.isIframeBlank(e)||(e.removeEventListener("load",a),r.getIframeContents(e,t,n))}catch(e){n()}}};e.addEventListener("load",a),o=setTimeout(a,this.iframesTimeout)}},{key:"onIframeReady",value:function(e,t,n){try{"complete"===e.contentWindow.document.readyState?this.isIframeBlank(e)?this.observeIframeLoad(e,t,n):this.getIframeContents(e,t,n):this.observeIframeLoad(e,t,n)}catch(e){n()}}},{key:"waitForIframes",value:function(e,t){var n=this,r=0;this.forEachIframe(e,function(){return!0},function(e){r++,n.waitForIframes(e.querySelector("html"),function(){--r||t()})},function(e){e||t()})}},{key:"forEachIframe",value:function(t,n,r){var i=this,o=arguments.length>3&&void 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o=t[i],a="disabled"!==this.opt.wildcards?this.setupWildcardsRegExp(i):this.escapeStr(i),s="disabled"!==this.opt.wildcards?this.setupWildcardsRegExp(o):this.escapeStr(o);""!==a&&""!==s&&(e=e.replace(new RegExp("("+this.escapeStr(a)+"|"+this.escapeStr(s)+")","gm"+n),r+"("+this.processSynomyms(a)+"|"+this.processSynomyms(s)+")"+r))}return e}},{key:"processSynomyms",value:function(e){return(this.opt.ignoreJoiners||this.opt.ignorePunctuation.length)&&(e=this.setupIgnoreJoinersRegExp(e)),e}},{key:"setupWildcardsRegExp",value:function(e){return(e=e.replace(/(?:\\)*\?/g,function(e){return"\\"===e.charAt(0)?"?":"
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-<meta name="description" content="Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.">
 <title>decoupleR: Ensemble of computational methods to infer biological activities from omics data • decoupleR</title>
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 <meta property="og:title" content="decoupleR: Ensemble of computational methods to infer biological activities from omics data">
+<meta name="description" content="Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.">
 <meta property="og:description" content="Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.">
 <meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg">
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@@ -34,67 +31,42 @@
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+<li class="nav-item"><a class="nav-link" href="articles/decoupleR.html">Get started</a></li>
+<li class="nav-item"><a class="nav-link" href="reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
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-    <a class="dropdown-item" href="articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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-<li class="nav-item">
-  <a class="nav-link" href="news/index.html">Changelog</a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul>
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+<li class="nav-item"><a class="nav-link" href="news/index.html">Changelog</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
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+<ul class="navbar-nav">
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 </nav><div class="container template-home">
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@@ -198,21 +170,19 @@ <h2 data-toc-skip>Developers</h2>
 
 
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
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-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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new file mode 100644
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new file mode 100644
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+/*!
+ * Color mode toggler for Bootstrap's docs (https://getbootstrap.com/)
+ * Copyright 2011-2023 The Bootstrap Authors
+ * Licensed under the Creative Commons Attribution 3.0 Unported License.
+ * Updates for {pkgdown} by the {bslib} authors, also licensed under CC-BY-3.0.
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Changelog"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -10,68 +7,42 @@
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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 </nav><div class="container template-news">
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Changelog</h1>
-      <small>Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
+      <small>Source: <a href="https://github.com/saezlab/decoupleR/blob/master/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
     </div>
 
     <div class="section level2">
@@ -217,7 +188,7 @@ <h4 id="methods-1-1">Methods<a class="anchor" aria-label="anchor" href="#methods
 <li>New <code>run_mean()</code> calculates both the unnormalized regulatory activity and the normalized (i.e. z-score) one based on an empirical distribution.</li>
 <li>New <code><a href="../reference/run_ora.html">run_ora()</a></code> fisher exact test to calculate the regulatory activity.</li>
 <li>New <code>run_pscira()</code> uses a logic equivalent to <code>run_mean()</code> with the difference that it does not accept a column of likelihood.</li>
-<li>New <code>run_scira()</code> calculates the regulatory activity through the coefficient <span class="math inline"><em>β</em><sub>1</sub></span> of an adjusted linear model.</li>
+<li>New <code>run_scira()</code> calculates the regulatory activity through the coefficient <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><msub><mi>β</mi><mn>1</mn></msub><annotation encoding="application/x-tex">\beta_1</annotation></semantics></math> of an adjusted linear model.</li>
 <li>New <code><a href="../reference/run_viper.html">run_viper()</a></code> incorporate a convinient wrapper for <a href="https://rdrr.io/bioc/viper/man/viper.html" class="external-link">viper::viper()</a>.</li>
 </ul></li>
 </ul></div>
@@ -236,23 +207,23 @@ <h4 id="converters-1-1">Converters<a class="anchor" aria-label="anchor" href="#c
 </ul></div>
 </div>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
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diff --git a/pkgdown.js b/pkgdown.js
index 5fccd9c0..1a99c65f 100644
--- a/pkgdown.js
+++ b/pkgdown.js
@@ -30,10 +30,10 @@
   /* Clipboard --------------------------*/
 
   function changeTooltipMessage(element, msg) {
-    var tooltipOriginalTitle=element.getAttribute('data-original-title');
-    element.setAttribute('data-original-title', msg);
+    var tooltipOriginalTitle=element.getAttribute('data-bs-original-title');
+    element.setAttribute('data-bs-original-title', msg);
     $(element).tooltip('show');
-    element.setAttribute('data-original-title', tooltipOriginalTitle);
+    element.setAttribute('data-bs-original-title', tooltipOriginalTitle);
   }
 
   if(ClipboardJS.isSupported()) {
@@ -60,7 +60,7 @@
         e.clearSelection();
       });
 
-      clipboard.on('error', function() {
+      clipboard.on('error', function(e) {
         changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
       });
 
@@ -153,4 +153,10 @@ async function searchFuse(query, callback) {
   });
 })(window.jQuery || window.$)
 
-
+document.addEventListener('keydown', function(event) {
+  // Check if the pressed key is '/'
+  if (event.key === '/') {
+    event.preventDefault();  // Prevent any default action associated with the '/' key
+    document.getElementById('search-input').focus();  // Set focus to the search input
+  }
+});
diff --git a/pkgdown.yml b/pkgdown.yml
index 9acada6b..bea4bc98 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -1,5 +1,5 @@
-pandoc: 3.1.1
-pkgdown: 2.0.8
+pandoc: '3.4'
+pkgdown: 2.1.1
 pkgdown_sha: ~
 articles:
   decoupleR: decoupleR.html
@@ -7,8 +7,7 @@ articles:
   pw_sc: pw_sc.html
   tf_bk: tf_bk.html
   tf_sc: tf_sc.html
-last_built: 2024-04-11T15:20Z
+last_built: 2024-10-19T12:59Z
 urls:
   reference: https://saezlab.github.io/decoupleR/reference
   article: https://saezlab.github.io/decoupleR/articles
-
diff --git a/reference/.data.html b/reference/.data.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/.data.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
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+
diff --git a/reference/Rplot001.png b/reference/Rplot001.png
deleted file mode 100644
index 17a35806..00000000
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diff --git a/reference/abort.html b/reference/abort.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/abort.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
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+
diff --git a/reference/as_label.html b/reference/as_label.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/as_label.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/as_name.html b/reference/as_name.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/as_name.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
+    <meta name="robots" content="noindex">
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+</html>
+
diff --git a/reference/check_corr.html b/reference/check_corr.html
index a3e06422..b2e3abf0 100644
--- a/reference/check_corr.html
+++ b/reference/check_corr.html
@@ -1,8 +1,5 @@
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+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Check correlation (colinearity)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
       <div class="d-none name"><code>check_corr.Rd</code></div>
     </div>
 
@@ -92,31 +63,31 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>network</dt>
+
+
+<dl><dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Correlation pairs tibble.</p>
+    <p>Correlation pairs tibble.</p>
     </div>
 
     <div class="section level2">
@@ -132,23 +103,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> T1     T2            -<span style="color: #BB0000;">0.688</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/convert_f_defaults.html b/reference/convert_f_defaults.html
index c5b20c07..b09d13bf 100644
--- a/reference/convert_f_defaults.html
+++ b/reference/convert_f_defaults.html
@@ -1,12 +1,9 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="convert_f_defaults() combine the dplyr::rename() way of
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Rename columns and add defaults values if column not present — convert_f_defaults • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Rename columns and add defaults values if column not present — convert_f_defaults"><meta name="description" content="convert_f_defaults() combine the dplyr::rename() way of
 working and with the tibble::add_column() to add columns
-with default values in case they don't exist after renaming data."><title>Rename columns and add defaults values if column not present — convert_f_defaults • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Rename columns and add defaults values if column not present — convert_f_defaults"><meta property="og:description" content="convert_f_defaults() combine the dplyr::rename() way of
+with default values in case they don't exist after renaming data."><meta property="og:description" content="convert_f_defaults() combine the dplyr::rename() way of
 working and with the tibble::add_column() to add columns
-with default values in case they don't exist after renaming data."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+with default values in case they don't exist after renaming data."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
   window.dataLayer = window.dataLayer || [];
   function gtag(){dataLayer.push(arguments);}
   gtag('js', new Date());
@@ -14,68 +11,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
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       <span class="navbar-toggler-icon"></span>
     </button>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Rename columns and add defaults values if column not present</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-dataset-converters.R" class="external-link"><code>R/utils-dataset-converters.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-dataset-converters.R" class="external-link"><code>R/utils-dataset-converters.R</code></a></small>
       <div class="d-none name"><code>convert_f_defaults.Rd</code></div>
     </div>
 
@@ -92,33 +63,33 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.data</dt>
+
+
+<dl><dt id="arg--data">.data<a class="anchor" aria-label="anchor" href="#arg--data"></a></dt>
 <dd><p>A data frame, data frame extension (e.g. a tibble), or a
 lazy data frame (e.g. from dbplyr or dtplyr). See <em>Methods</em>, below, for
 more details.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>For <code>rename()</code>: &lt;<code><a href="https://dplyr.tidyverse.org/reference/dplyr_tidy_select.html" class="external-link">tidy-select</a></code>&gt; Use
 <code>new_name = old_name</code> to rename selected variables.</p>
 <p>For <code>rename_with()</code>: additional arguments passed onto <code>.fn</code>.</p></dd>
 
 
-<dt>.def_col_val</dt>
+<dt id="arg--def-col-val">.def_col_val<a class="anchor" aria-label="anchor" href="#arg--def-col-val"></a></dt>
 <dd><p>Named vector with columns with default values
 if none exist after rename.</p></dd>
 
 
-<dt>.use_dots</dt>
+<dt id="arg--use-dots">.use_dots<a class="anchor" aria-label="anchor" href="#arg--use-dots"></a></dt>
 <dd><p>Should a dot prefix be added to renamed variables?
 This will allow swapping of columns.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>An object of the same type as .data. The output has the following properties:</p><ul><li><p>Rows are not affected.</p></li>
+    <p>An object of the same type as .data. The output has the following properties:</p><ul><li><p>Rows are not affected.</p></li>
 <li><p>Column names are changed.</p></li>
 <li><p>Column order is the same as that of the function call.</p></li>
 </ul></div>
@@ -153,23 +124,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1     2     3</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/decouple.html b/reference/decouple.html
index 7ae66457..75605971 100644
--- a/reference/decouple.html
+++ b/reference/decouple.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculate the source activity per sample out of a gene expression matrix by
-coupling a regulatory network with a variety of statistics."><title>Evaluate multiple statistics with same input data — decouple • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Evaluate multiple statistics with same input data — decouple"><meta property="og:description" content="Calculate the source activity per sample out of a gene expression matrix by
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Evaluate multiple statistics with same input data — decouple • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Evaluate multiple statistics with same input data — decouple"><meta name="description" content="Calculate the source activity per sample out of a gene expression matrix by
+coupling a regulatory network with a variety of statistics."><meta property="og:description" content="Calculate the source activity per sample out of a gene expression matrix by
+coupling a regulatory network with a variety of statistics."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -12,68 +9,42 @@
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 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
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-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
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-
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Evaluate multiple statistics with same input data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-decouple.R" class="external-link"><code>R/decoupleR-decouple.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-decouple.R" class="external-link"><code>R/decoupleR-decouple.R</code></a></small>
       <div class="d-none name"><code>decouple.Rd</code></div>
     </div>
 
@@ -101,43 +72,45 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>statistics</dt>
+<dt id="arg-statistics">statistics<a class="anchor" aria-label="anchor" href="#arg-statistics"></a></dt>
 <dd><p>Statistical methods to be run sequentially. If none are
 provided, only top performer methods are run (mlm, ulm and wsum).</p></dd>
 
 
-<dt>args</dt>
+<dt id="arg-args">args<a class="anchor" aria-label="anchor" href="#arg-args"></a></dt>
 <dd><p>A list of argument-lists the same length as <code>statistics</code>
 (or length 1). The default argument, list(NULL), will be recycled to the
 same length as <code>statistics</code>, and will call each function with no arguments
 (apart from <code>mat</code>, <code>network</code>, <code>.source</code> and, <code>.target</code>).</p></dd>
 
 
-<dt>consensus_score</dt>
+<dt id="arg-consensus-score">consensus_score<a class="anchor" aria-label="anchor" href="#arg-consensus-score"></a></dt>
 <dd><p>Boolean whether to run a consensus score between
 methods.</p></dd>
 
 
-<dt>consensus_stats</dt>
+<dt id="arg-consensus-stats">consensus_stats<a class="anchor" aria-label="anchor" href="#arg-consensus-stats"></a></dt>
 <dd><p>List of estimate names to use for the calculation
 of the consensus score. This is used to filter out extra estimations
 from some methods, for example wsum returns wsum, corr_wsum and norm_wsum. If
@@ -146,23 +119,21 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 estimates after running all methods in the statistics argument.</p></dd>
 
 
-<dt>include_time</dt>
+<dt id="arg-include-time">include_time<a class="anchor" aria-label="anchor" href="#arg-include-time"></a></dt>
 <dd><p>Should the time per statistic evaluated be informed?</p></dd>
 
 
-<dt>show_toy_call</dt>
+<dt id="arg-show-toy-call">show_toy_call<a class="anchor" aria-label="anchor" href="#arg-show-toy-call"></a></dt>
 <dd><p>The call of each statistic must be informed?</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>run_id</code>: Indicates the order in which the methods have been executed.</p></li>
 <li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
@@ -173,7 +144,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 </ol></div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
 <code><a href="run_gsva.html">run_gsva</a>()</code>,
@@ -212,23 +183,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
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 </div>
 
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diff --git a/reference/decoupleR-package.html b/reference/decoupleR-package.html
index c85d01b0..49a0be99 100644
--- a/reference/decoupleR-package.html
+++ b/reference/decoupleR-package.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase."><title>decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package"><meta property="og:description" content="Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. 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       <img src="../logo.svg" class="logo" alt=""><h1>decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-package.R" class="external-link"><code>R/decoupleR-package.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-package.R" class="external-link"><code>R/decoupleR-package.R</code></a></small>
       <div class="d-none name"><code>decoupleR-package.Rd</code></div>
     </div>
 
@@ -101,23 +72,23 @@ <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a><
 <li><p>Julio Saez-Rodriguez <a href="mailto:pub.saez@uni-heidelberg.de">pub.saez@uni-heidelberg.de</a> (<a href="https://orcid.org/0000-0002-8552-8976" class="external-link">ORCID</a>)</p></li>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/reference/decoupleR.html b/reference/decoupleR.html
new file mode 100644
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@@ -0,0 +1,8 @@
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index 36e5b863..2f3e7607 100644
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+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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       <img src="../logo.svg" class="logo" alt=""><h1>DecoupleR mat format</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-decoupler-formats.R" class="external-link"><code>R/utils-decoupler-formats.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-decoupler-formats.R" class="external-link"><code>R/utils-decoupler-formats.R</code></a></small>
       <div class="d-none name"><code>dot-decoupler_mat_format.Rd</code></div>
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@@ -82,7 +53,9 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
@@ -91,27 +64,27 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 </dl></div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR formats: 
+    <div class="dont-index"><p>Other decoupleR formats:
 <code><a href="dot-decoupler_network_format.html">.decoupler_network_format</a></code></p></div>
     </div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/reference/dot-decoupler_network_format.html b/reference/dot-decoupler_network_format.html
index 280a2d80..9fb6f1eb 100644
--- a/reference/dot-decoupler_network_format.html
+++ b/reference/dot-decoupler_network_format.html
@@ -1,12 +1,9 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="A network passed to any run_ method in the package must contain at
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>DecoupleR network format — .decoupler_network_format • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="DecoupleR network format — .decoupler_network_format"><meta name="description" content="A network passed to any run_ method in the package must contain at
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+the methods must map their corresponding metadata associated with their edges."><meta property="og:description" content="A network passed to any run_ method in the package must contain at
 least two attributes: .source and .target. In addition,
-the methods must map their corresponding metadata associated with their edges."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>DecoupleR network format</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-decoupler-formats.R" class="external-link"><code>R/utils-decoupler-formats.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-decoupler-formats.R" class="external-link"><code>R/utils-decoupler-formats.R</code></a></small>
       <div class="d-none name"><code>dot-decoupler_network_format.Rd</code></div>
     </div>
 
@@ -88,29 +59,31 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>network</dt>
+
+
+<dl><dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    
+
 <ul><li><p>All the attributes to be mapped are prefixed by <code>.</code></p></li>
 <li><p>The idea of using this type of mapping is to provide flexibility to
 different types of networks, be they regulatory, metabolic, or of any
@@ -120,27 +93,27 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
 </ul></div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR formats: 
+    <div class="dont-index"><p>Other decoupleR formats:
 <code><a href="dot-decoupler_mat_format.html">.decoupler_mat_format</a></code></p></div>
     </div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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     </footer></div>
 
-  
 
-  
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diff --git a/reference/dot-fit_preprocessing.html b/reference/dot-fit_preprocessing.html
index 76e46769..43a10683 100644
--- a/reference/dot-fit_preprocessing.html
+++ b/reference/dot-fit_preprocessing.html
@@ -1,18 +1,15 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Pre-processing for methods that fit networks. — .fit_preprocessing • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pre-processing for methods that fit networks. — .fit_preprocessing"><meta name="description" content="
 
 If center is true, then the expression values are centered by the
 mean of expression across the samples.
 
-"><title>Pre-processing for methods that fit networks. — .fit_preprocessing • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pre-processing for methods that fit networks. — .fit_preprocessing"><meta property="og:description" content="
+"><meta property="og:description" content="
 
 If center is true, then the expression values are centered by the
 mean of expression across the samples.
 
-"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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   gtag('js', new Date());
@@ -20,73 +17,47 @@
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 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Pre-processing for methods that fit networks.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
       <div class="d-none name"><code>dot-fit_preprocessing.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    
+
 <ul><li><p>If <code>center</code> is true, then the expression values are centered by the
 mean of expression across the samples.</p></li>
 </ul></div>
@@ -98,36 +69,36 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>network</dt>
+
+
+<dl><dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>mat</dt>
+<dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>center</dt>
+<dt id="arg-center">center<a class="anchor" aria-label="anchor" href="#arg-center"></a></dt>
 <dd><p>Logical value indicating if <code>mat</code> must be centered by
 <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>.</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>Should missing values (including NaN) be omitted from the
 calculations of <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>?</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Deprecated parameter.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A named list of matrices to evaluate in methods that fit models, like
+    <p>A named list of matrices to evaluate in methods that fit models, like
 <code>.mlm_analysis()</code>.</p><ul><li><p>mat: Features as rows and samples as columns.</p></li>
 <li><p>mor_mat: Features as rows and columns as source.</p></li>
 </ul></div>
@@ -210,23 +181,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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new file mode 100644
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@@ -0,0 +1,8 @@
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diff --git a/reference/extract_sets.html b/reference/extract_sets.html
index 35f5045f..899e5cf2 100644
--- a/reference/extract_sets.html
+++ b/reference/extract_sets.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Extracts feature sets from a renamed network (see rename_net)."><title>Extract sets — extract_sets • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Extract sets — extract_sets"><meta property="og:description" content="Extracts feature sets from a renamed network (see rename_net)."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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       <img src="../logo.svg" class="logo" alt=""><h1>Extract sets</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-dataset-converters.R" class="external-link"><code>R/utils-dataset-converters.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-dataset-converters.R" class="external-link"><code>R/utils-dataset-converters.R</code></a></small>
       <div class="d-none name"><code>extract_sets.Rd</code></div>
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@@ -86,7 +57,9 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>network</dt>
+
+
+<dl><dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 </dl></div>
@@ -109,23 +82,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 </code></pre></div>
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-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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       <img src="../logo.svg" class="logo" alt=""><h1>Filter sources with minsize targets</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
       <div class="d-none name"><code>filt_minsize.Rd</code></div>
     </div>
 
@@ -86,23 +57,23 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat_f_names</dt>
+
+
+<dl><dt id="arg-mat-f-names">mat_f_names<a class="anchor" aria-label="anchor" href="#arg-mat-f-names"></a></dt>
 <dd><p>Feature names of mat.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Filtered network.</p>
+    <p>Filtered network.</p>
     </div>
 
     <div class="section level2">
@@ -121,23 +92,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> T3     G11      1            1</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/get_collectri.html b/reference/get_collectri.html
index 1e93c027..3bb4e8a5 100644
--- a/reference/get_collectri.html
+++ b/reference/get_collectri.html
@@ -1,16 +1,13 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="CollecTRI gene regulatory network.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri"><meta name="description" content="CollecTRI gene regulatory network.
 Wrapper to access CollecTRI gene regulatory network. CollecTRI is a
 comprehensive resource containing a curated collection of transcription
 factors (TFs) and their target genes. It is an expansion of DoRothEA.
-Each interaction is weighted by its mode of regulation (either positive or negative)."><title>CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri"><meta property="og:description" content="CollecTRI gene regulatory network.
+Each interaction is weighted by its mode of regulation (either positive or negative)."><meta property="og:description" content="CollecTRI gene regulatory network.
 Wrapper to access CollecTRI gene regulatory network. CollecTRI is a
 comprehensive resource containing a curated collection of transcription
 factors (TFs) and their target genes. It is an expansion of DoRothEA.
-Each interaction is weighted by its mode of regulation (either positive or negative)."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
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+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative).</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
       <div class="d-none name"><code>get_collectri.Rd</code></div>
     </div>
 
@@ -98,16 +69,18 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>organism</dt>
+
+
+<dl><dt id="arg-organism">organism<a class="anchor" aria-label="anchor" href="#arg-organism"></a></dt>
 <dd><p>Which organism to use. Only human, mouse and rat are available.</p></dd>
 
 
-<dt>split_complexes</dt>
+<dt id="arg-split-complexes">split_complexes<a class="anchor" aria-label="anchor" href="#arg-split-complexes"></a></dt>
 <dd><p>Whether to split complexes into subunits. By default
 complexes are kept as they are.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Ignored.</p></dd>
 
 </dl></div>
@@ -117,23 +90,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">collectri</span> <span class="op">&lt;-</span> <span class="fu">get_collectri</span><span class="op">(</span>organism<span class="op">=</span><span class="st">'human'</span>, split_complexes<span class="op">=</span><span class="cn">FALSE</span><span class="op">)</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/get_dorothea.html b/reference/get_dorothea.html
index 93dec278..fcd66463 100644
--- a/reference/get_dorothea.html
+++ b/reference/get_dorothea.html
@@ -1,14 +1,11 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Wrapper to access DoRothEA gene regulatory network. DoRothEA is a
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>DoRothEA gene regulatory network. — get_dorothea • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="DoRothEA gene regulatory network. — get_dorothea"><meta name="description" content="Wrapper to access DoRothEA gene regulatory network. DoRothEA is a
 comprehensive resource containing a curated collection of transcription
 factors (TFs) and their target genes. Each interaction is weighted by its
-mode of regulation (either positive or negative) and by its confidence level"><title>DoRothEA gene regulatory network. — get_dorothea • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="DoRothEA gene regulatory network. — get_dorothea"><meta property="og:description" content="Wrapper to access DoRothEA gene regulatory network. DoRothEA is a
+mode of regulation (either positive or negative) and by its confidence level"><meta property="og:description" content="Wrapper to access DoRothEA gene regulatory network. DoRothEA is a
 comprehensive resource containing a curated collection of transcription
 factors (TFs) and their target genes. Each interaction is weighted by its
-mode of regulation (either positive or negative) and by its confidence level"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+mode of regulation (either positive or negative) and by its confidence level"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -16,68 +13,42 @@
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 </script></head><body>
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-    
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>DoRothEA gene regulatory network.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
       <div class="d-none name"><code>get_dorothea.Rd</code></div>
     </div>
 
@@ -99,16 +70,18 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>organism</dt>
+
+
+<dl><dt id="arg-organism">organism<a class="anchor" aria-label="anchor" href="#arg-organism"></a></dt>
 <dd><p>Which organism to use. Only human, mouse and rat are available.</p></dd>
 
 
-<dt>levels</dt>
+<dt id="arg-levels">levels<a class="anchor" aria-label="anchor" href="#arg-levels"></a></dt>
 <dd><p>List of confidence levels to return. Goes from A to D, A
 being the most confident and D being the less.</p></dd>
 
 
-<dt>weight_dict</dt>
+<dt id="arg-weight-dict">weight_dict<a class="anchor" aria-label="anchor" href="#arg-weight-dict"></a></dt>
 <dd><p>Dictionary of values to divide the mode of regulation
 (-1 or 1), one for each confidence level. Bigger values will generate
 weights close to zero.</p></dd>
@@ -120,23 +93,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">dorothea</span> <span class="op">&lt;-</span> <span class="fu">get_dorothea</span><span class="op">(</span>organism<span class="op">=</span><span class="st">'human'</span>, levels<span class="op">=</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">'A'</span>, <span class="st">'B'</span><span class="op">)</span><span class="op">)</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
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   </body></html>
 
diff --git a/reference/get_ksn_omnipath.html b/reference/get_ksn_omnipath.html
index a5a3e7b1..6a84fed9 100644
--- a/reference/get_ksn_omnipath.html
+++ b/reference/get_ksn_omnipath.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Retrieve a ready to use, curated kinase-substrate Network from the OmniPath
-database."><title>OmniPath kinase-substrate network — get_ksn_omnipath • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="OmniPath kinase-substrate network — get_ksn_omnipath"><meta property="og:description" content="Retrieve a ready to use, curated kinase-substrate Network from the OmniPath
-database."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>OmniPath kinase-substrate network — get_ksn_omnipath • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="OmniPath kinase-substrate network — get_ksn_omnipath"><meta name="description" content="Retrieve a ready to use, curated kinase-substrate Network from the OmniPath
+database."><meta property="og:description" content="Retrieve a ready to use, curated kinase-substrate Network from the OmniPath
+database."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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   gtag('js', new Date());
@@ -12,68 +9,42 @@
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 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
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+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>OmniPath kinase-substrate network</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
       <div class="d-none name"><code>get_ksn_omnipath.Rd</code></div>
     </div>
 
@@ -89,7 +60,9 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
+
+
+<dl><dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Passed to <code><a href="https://saezlab.github.io/OmnipathR/reference/import_omnipath_enzsub.html" class="external-link">OmnipathR::import_omnipath_enzsub</a></code>.</p></dd>
 
 </dl></div>
@@ -100,23 +73,23 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
 functions.</p>
     </div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/get_profile_of.html b/reference/get_profile_of.html
index 9aacf71f..4975d406 100644
--- a/reference/get_profile_of.html
+++ b/reference/get_profile_of.html
@@ -1,12 +1,9 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Turns implicit missing values into explicit missing values. This is a wrapper
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Complete a data frame with missing combinations of data — get_profile_of • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Complete a data frame with missing combinations of data — get_profile_of"><meta name="description" content="Turns implicit missing values into explicit missing values. This is a wrapper
 around expand(), dplyr::full_join() and replace_na() that's useful for
-completing missing combinations of data."><title>Complete a data frame with missing combinations of data — get_profile_of • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Complete a data frame with missing combinations of data — get_profile_of"><meta property="og:description" content="Turns implicit missing values into explicit missing values. This is a wrapper
+completing missing combinations of data."><meta property="og:description" content="Turns implicit missing values into explicit missing values. This is a wrapper
 around expand(), dplyr::full_join() and replace_na() that's useful for
-completing missing combinations of data."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+completing missing combinations of data."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -14,68 +11,42 @@
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
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-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Complete a data frame with missing combinations of data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-profiles.R" class="external-link"><code>R/utils-profiles.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-profiles.R" class="external-link"><code>R/utils-profiles.R</code></a></small>
       <div class="d-none name"><code>get_profile_of.Rd</code></div>
     </div>
 
@@ -92,16 +63,18 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
+
+
+<dl><dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
 <dd><p>A data frame.</p></dd>
 
 
-<dt>sources</dt>
+<dt id="arg-sources">sources<a class="anchor" aria-label="anchor" href="#arg-sources"></a></dt>
 <dd><p>A named vector or list with the values to expand and get
 profile.</p></dd>
 
 
-<dt>values_fill</dt>
+<dt id="arg-values-fill">values_fill<a class="anchor" aria-label="anchor" href="#arg-values-fill"></a></dt>
 <dd><p>Optionally, a (scalar) value that specifies what each
 <code>value</code> should be filled in with when missing.</p>
 <p>This can be a named list if you want to apply different fill values to
@@ -110,9 +83,7 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A data frame with the expanded grid of the values passed in
+    <p>A data frame with the expanded grid of the values passed in
 <code>sources</code> and filled as specified in the <code>fill</code> argument.</p>
     </div>
     <div class="section level2">
@@ -122,7 +93,7 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
 
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># \dontrun{</span></span></span>
 <span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span>, warn.conflicts <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></span><span class="op">(</span></span></span>
 <span class="r-in"><span>    group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">2</span>, <span class="fl">1</span><span class="op">)</span>,</span></span>
@@ -147,26 +118,26 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Replace all NAs with "Unkwnon"</span></span></span>
 <span class="r-in"><span><span class="va">df</span> <span class="op"><a href="pipe.html">%&gt;%</a></span> <span class="fu">get_profile_of</span><span class="op">(</span>sources <span class="op">=</span> <span class="va">to_get_profile</span>, values_fill <span class="op">=</span> <span class="st">"Unknown"</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
+<span class="r-in"><span><span class="op">}</span> <span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/get_progeny.html b/reference/get_progeny.html
index f60fb304..f5ade651 100644
--- a/reference/get_progeny.html
+++ b/reference/get_progeny.html
@@ -1,12 +1,9 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Wrapper to access PROGENy model gene weights. Each pathway is defined with a
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny"><meta name="description" content="Wrapper to access PROGENy model gene weights. Each pathway is defined with a
 collection of target genes, each interaction has an associated p-value and
-weight. The top significant interactions per pathway are returned."><title>Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny"><meta property="og:description" content="Wrapper to access PROGENy model gene weights. Each pathway is defined with a
+weight. The top significant interactions per pathway are returned."><meta property="og:description" content="Wrapper to access PROGENy model gene weights. Each pathway is defined with a
 collection of target genes, each interaction has an associated p-value and
-weight. The top significant interactions per pathway are returned."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+weight. The top significant interactions per pathway are returned."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -14,68 +11,42 @@
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+
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
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-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Pathway RespOnsive GENes for activity inference (PROGENy).</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
       <div class="d-none name"><code>get_progeny.Rd</code></div>
     </div>
 
@@ -92,11 +63,13 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>organism</dt>
+
+
+<dl><dt id="arg-organism">organism<a class="anchor" aria-label="anchor" href="#arg-organism"></a></dt>
 <dd><p>Which organism to use. Only human and mouse are available.</p></dd>
 
 
-<dt>top</dt>
+<dt id="arg-top">top<a class="anchor" aria-label="anchor" href="#arg-top"></a></dt>
 <dd><p>Number of genes per pathway to return.</p></dd>
 
 </dl></div>
@@ -106,23 +79,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">progeny</span> <span class="op">&lt;-</span> <span class="fu">get_progeny</span><span class="op">(</span>organism<span class="op">=</span><span class="st">'human'</span>, top<span class="op">=</span><span class="fl">500</span><span class="op">)</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/get_resource.html b/reference/get_resource.html
index 1e00d7c0..da79ec65 100644
--- a/reference/get_resource.html
+++ b/reference/get_resource.html
@@ -1,14 +1,11 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Wrapper to access resources inside Omnipath.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource"><meta name="description" content="Wrapper to access resources inside Omnipath.
 This wrapper allows to easily query different prior knowledge resources.
 To check available resources run decoupleR::show_resources(). For more
-information visit the official website for Omnipath."><title>Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource"><meta property="og:description" content="Wrapper to access resources inside Omnipath.
+information visit the official website for Omnipath."><meta property="og:description" content="Wrapper to access resources inside Omnipath.
 This wrapper allows to easily query different prior knowledge resources.
 To check available resources run decoupleR::show_resources(). For more
-information visit the official website for Omnipath."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+information visit the official website for Omnipath."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run <code>decoupleR::show_resources()</code>. For more information visit the official website for <a href="https://omnipathdb.org/" class="external-link">Omnipath</a>.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
       <div class="d-none name"><code>get_resource.Rd</code></div>
     </div>
 
@@ -95,15 +66,17 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>name</dt>
+
+
+<dl><dt id="arg-name">name<a class="anchor" aria-label="anchor" href="#arg-name"></a></dt>
 <dd><p>Name of the resource to query.</p></dd>
 
 
-<dt>organism</dt>
+<dt id="arg-organism">organism<a class="anchor" aria-label="anchor" href="#arg-organism"></a></dt>
 <dd><p>Organism name or NCBI Taxonomy ID.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Passed to <code><a href="https://saezlab.github.io/OmnipathR/reference/import_omnipath_annotations.html" class="external-link">OmnipathR::import_omnipath_annotations</a></code>.</p></dd>
 
 </dl></div>
@@ -113,23 +86,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">decoupleR</span><span class="fu">::</span><span class="fu">get_resource</span><span class="op">(</span><span class="st">'SIGNOR'</span><span class="op">)</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/get_toy_data.html b/reference/get_toy_data.html
index cdf74a94..6c4128e8 100644
--- a/reference/get_toy_data.html
+++ b/reference/get_toy_data.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Generate a toy mat and network."><title>Generate a toy mat and network. — get_toy_data • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Generate a toy mat and network. — get_toy_data"><meta property="og:description" content="Generate a toy mat and network."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Generate a toy mat and network. — get_toy_data • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Generate a toy mat and network. — get_toy_data"><meta name="description" content="Generate a toy mat and network."><meta property="og:description" content="Generate a toy mat and network."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -10,68 +7,42 @@
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 </script></head><body>
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Generate a toy <code>mat</code> and <code>network</code>.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
       <div class="d-none name"><code>get_toy_data.Rd</code></div>
     </div>
 
@@ -86,20 +57,20 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>n_samples</dt>
+
+
+<dl><dt id="arg-n-samples">n_samples<a class="anchor" aria-label="anchor" href="#arg-n-samples"></a></dt>
 <dd><p>Number of samples to simulate.</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>List containing <code>mat</code> and <code>network</code>.</p>
+    <p>List containing <code>mat</code> and <code>network</code>.</p>
     </div>
 
     <div class="section level2">
@@ -109,23 +80,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span><span class="va">network</span> <span class="op">&lt;-</span> <span class="va">data</span><span class="op">$</span><span class="va">network</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/reference/index.html b/reference/index.html
index 1da076c0..c386f04e 100644
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-      <img src="../logo.svg" class="logo" alt=""><h1>Function reference</h1>
+      <img src="../logo.svg" class="logo" alt=""><h1>Package index</h1>
     </div>
 
     <div class="section level2">
       <h2 id="decoupler">decoupleR<a class="anchor" aria-label="anchor" href="#decoupler"></a></h2>
-      
-      
 
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-      
-      
-      
+
+
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="decouple.html">decouple()</a></code> 
+
+          <code><a href="decouple.html">decouple()</a></code>
+
         </dt>
         <dd>Evaluate multiple statistics with same input data</dd>
       </dl></div><div class="section level2">
       <h2 id="statistics">Statistics<a class="anchor" aria-label="anchor" href="#statistics"></a></h2>
-      
-      
 
-      
-    </div><div id="" class="section level2">
-      
-      
-      
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+
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="run_aucell.html">run_aucell()</a></code> 
+
+          <code><a href="run_aucell.html">run_aucell()</a></code>
+
         </dt>
         <dd>AUCell</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_consensus.html">run_consensus()</a></code> 
+
+          <code><a href="run_consensus.html">run_consensus()</a></code>
+
         </dt>
         <dd>Consensus score between methods</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_fgsea.html">run_fgsea()</a></code> 
+
+          <code><a href="run_fgsea.html">run_fgsea()</a></code>
+
         </dt>
         <dd>Fast Gene Set Enrichment Analysis (FGSEA)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_gsva.html">run_gsva()</a></code> 
+
+          <code><a href="run_gsva.html">run_gsva()</a></code>
+
         </dt>
         <dd>Gene Set Variation Analysis (GSVA)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_mdt.html">run_mdt()</a></code> 
+
+          <code><a href="run_mdt.html">run_mdt()</a></code>
+
         </dt>
         <dd>Multivariate Decision Trees (MDT)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_mlm.html">run_mlm()</a></code> 
+
+          <code><a href="run_mlm.html">run_mlm()</a></code>
+
         </dt>
         <dd>Multivariate Linear Model (MLM)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_ora.html">run_ora()</a></code> 
+
+          <code><a href="run_ora.html">run_ora()</a></code>
+
         </dt>
         <dd>Over Representation Analysis (ORA)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_udt.html">run_udt()</a></code> 
+
+          <code><a href="run_udt.html">run_udt()</a></code>
+
         </dt>
         <dd>Univariate Decision Tree (UDT)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_ulm.html">run_ulm()</a></code> 
+
+          <code><a href="run_ulm.html">run_ulm()</a></code>
+
         </dt>
         <dd>Univariate Linear Model (ULM)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_viper.html">run_viper()</a></code> 
+
+          <code><a href="run_viper.html">run_viper()</a></code>
+
         </dt>
         <dd>Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_wmean.html">run_wmean()</a></code> 
+
+          <code><a href="run_wmean.html">run_wmean()</a></code>
+
         </dt>
         <dd>Weighted Mean (WMEAN)</dd>
       </dl><dl><dt>
-          
-          <code><a href="run_wsum.html">run_wsum()</a></code> 
+
+          <code><a href="run_wsum.html">run_wsum()</a></code>
+
         </dt>
         <dd>Weighted Sum (WSUM)</dd>
       </dl></div><div class="section level2">
       <h2 id="network-converters">Network converters<a class="anchor" aria-label="anchor" href="#network-converters"></a></h2>
-      
-      
 
-      
-    </div><div id="" class="section level2">
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-      
-      
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+
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="convert_f_defaults.html">convert_f_defaults()</a></code> 
+
+          <code><a href="convert_f_defaults.html">convert_f_defaults()</a></code>
+
         </dt>
         <dd>Rename columns and add defaults values if column not present</dd>
       </dl><dl><dt>
-          
-          <code><a href="rename_net.html">rename_net()</a></code> 
+
+          <code><a href="rename_net.html">rename_net()</a></code>
+
         </dt>
         <dd>Rename network</dd>
       </dl><dl><dt>
-          
-          <code><a href="extract_sets.html">extract_sets()</a></code> 
+
+          <code><a href="extract_sets.html">extract_sets()</a></code>
+
         </dt>
         <dd>Extract sets</dd>
       </dl></div><div class="section level2">
       <h2 id="utils">Utils<a class="anchor" aria-label="anchor" href="#utils"></a></h2>
-      
-      
 
-      
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-      
-      
-      
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+    </div><div class="section level2">
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+
 
       <dl><dt>
-          
-          <code><a href="check_corr.html">check_corr()</a></code> 
+
+          <code><a href="check_corr.html">check_corr()</a></code>
+
         </dt>
         <dd>Check correlation (colinearity)</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_toy_data.html">get_toy_data()</a></code> 
+
+          <code><a href="get_toy_data.html">get_toy_data()</a></code>
+
         </dt>
         <dd>Generate a toy <code>mat</code> and <code>network</code>.</dd>
       </dl><dl><dt>
-          
-          <code><a href="show_methods.html">show_methods()</a></code> 
+
+          <code><a href="show_methods.html">show_methods()</a></code>
+
         </dt>
         <dd>Show methods</dd>
       </dl><dl><dt>
-          
-          <code><a href="dot-fit_preprocessing.html">.fit_preprocessing()</a></code> 
+
+          <code><a href="dot-fit_preprocessing.html">.fit_preprocessing()</a></code>
+
         </dt>
         <dd>Pre-processing for methods that fit networks.</dd>
       </dl><dl><dt>
-          
-          <code><a href="filt_minsize.html">filt_minsize()</a></code> 
+
+          <code><a href="filt_minsize.html">filt_minsize()</a></code>
+
         </dt>
         <dd>Filter sources with minsize targets</dd>
       </dl><dl><dt>
-          
-          <code><a href="intersect_regulons.html">intersect_regulons()</a></code> 
+
+          <code><a href="intersect_regulons.html">intersect_regulons()</a></code>
+
         </dt>
         <dd>Intersect network target features with input matrix.</dd>
       </dl></div><div class="section level2">
       <h2 id="omnipath-wrappers">Omnipath wrappers<a class="anchor" aria-label="anchor" href="#omnipath-wrappers"></a></h2>
-      
-      
 
-      
-    </div><div id="" class="section level2">
-      
-      
-      
+
+
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="show_resources.html">show_resources()</a></code> 
+
+          <code><a href="show_resources.html">show_resources()</a></code>
+
         </dt>
         <dd>Shows available resources in Omnipath. For more information visit the official website for <a href="https://omnipathdb.org/" class="external-link">Omnipath</a>.</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_resource.html">get_resource()</a></code> 
+
+          <code><a href="get_resource.html">get_resource()</a></code>
+
         </dt>
         <dd>Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run <code><a href="../reference/show_resources.html">decoupleR::show_resources()</a></code>. For more information visit the official website for <a href="https://omnipathdb.org/" class="external-link">Omnipath</a>.</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_dorothea.html">get_dorothea()</a></code> 
+
+          <code><a href="get_dorothea.html">get_dorothea()</a></code>
+
         </dt>
         <dd>DoRothEA gene regulatory network.</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_collectri.html">get_collectri()</a></code> 
+
+          <code><a href="get_collectri.html">get_collectri()</a></code>
+
         </dt>
         <dd>CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative).</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_progeny.html">get_progeny()</a></code> 
+
+          <code><a href="get_progeny.html">get_progeny()</a></code>
+
         </dt>
         <dd>Pathway RespOnsive GENes for activity inference (PROGENy).</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_ksn_omnipath.html">get_ksn_omnipath()</a></code> 
+
+          <code><a href="get_ksn_omnipath.html">get_ksn_omnipath()</a></code>
+
         </dt>
         <dd>OmniPath kinase-substrate network</dd>
       </dl></div>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/reference/intersect_regulons.html b/reference/intersect_regulons.html
index fcda7c80..95aa08e0 100644
--- a/reference/intersect_regulons.html
+++ b/reference/intersect_regulons.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Keep only edges which its target features belong to the input matrix."><title>Intersect network target features with input matrix. — intersect_regulons • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Intersect network target features with input matrix. — intersect_regulons"><meta property="og:description" content="Keep only edges which its target features belong to the input matrix."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Intersect network target features with input matrix. — intersect_regulons • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Intersect network target features with input matrix. — intersect_regulons"><meta name="description" content="Keep only edges which its target features belong to the input matrix."><meta property="og:description" content="Keep only edges which its target features belong to the input matrix."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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       <img src="../logo.svg" class="logo" alt=""><h1>Intersect network target features with input matrix.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
       <div class="d-none name"><code>intersect_regulons.Rd</code></div>
     </div>
 
@@ -86,34 +57,34 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Minimum number of targets per source allowed.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Filtered tibble.</p>
+    <p>Filtered tibble.</p>
     </div>
 
     <div class="section level2">
@@ -132,23 +103,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> T3     G11      1  </span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/reference/mat_format.html b/reference/mat_format.html
new file mode 100644
index 00000000..fd30709f
--- /dev/null
+++ b/reference/mat_format.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/dot-decoupler_mat_format.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://saezlab.github.io/decoupleR/reference/dot-decoupler_mat_format.html">
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+
diff --git a/reference/network_format.html b/reference/network_format.html
new file mode 100644
index 00000000..d9717bc2
--- /dev/null
+++ b/reference/network_format.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html" />
+    <meta name="robots" content="noindex">
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+
diff --git a/reference/omnipathr-log/omnipathr-20240411-1520.log b/reference/omnipathr-log/omnipathr-20240411-1520.log
deleted file mode 100644
index b4df4cf7..00000000
--- a/reference/omnipathr-log/omnipathr-20240411-1520.log
+++ /dev/null
@@ -1,61 +0,0 @@
-[2024-04-11 15:20:19] [INFO]    [OmnipathR] Welcome to OmnipathR!
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Reading JSON from `/github/home/.cache/OmnipathR/cache.json` (encoding: UTF-8).
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:20:19] [INFO]    [OmnipathR] Initialized cache: `/github/home/.cache/OmnipathR`.
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/db/db_def.json` (encoding: UTF-8).
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/internal/magic_bytes.json` (encoding: UTF-8).
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/internal/urls.json` (encoding: UTF-8).
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/internal/id_types.json` (encoding: UTF-8).
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:20:19] [INFO]    [OmnipathR] Loading database `Ensembl and OMA organism names`.
-[2024-04-11 15:20:19] [INFO]    [OmnipathR] Looking up in cache `https://www.ensembl.org/info/about/species.html`: key=7332486db7400730697234bad76ca0c8e4d00799, latest version=1.
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Cache file path: /github/home/.cache/OmnipathR/7332486db7400730697234bad76ca0c8e4d00799-1.html
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Looking up in cache: `https://omabrowser.org/All/oma-species.txt`.
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/30e690cbb55dfc63b5903ab337f34ffc2f4be397-1.rds`.
-[2024-04-11 15:20:19] [INFO]    [OmnipathR] Loaded database `Ensembl and OMA organism names`.
-[2024-04-11 15:20:19] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=collectri&organisms=9606&dorothea_levels=A,B&fields=extra_attrs,evidences,sources,references,curation_effort&loops=yes&license=academic`
-[2024-04-11 15:20:20] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/5e82de18cbd9b5d9237867d70ab653aa2a24da2e-1.rds`.
-[2024-04-11 15:20:20] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=collectri&organisms=9606&dorothea_levels=A,B&fields=extra_attrs,evidences,sources,references,curation_effort&loops=yes&license=academic`
-[2024-04-11 15:20:20] [TRACE]   [OmnipathR] Converting JSON column `extra_attrs` to list.
-[2024-04-11 15:20:21] [TRACE]   [OmnipathR] Converting JSON column `evidences` to list.
-[2024-04-11 15:20:24] [TRACE]   [OmnipathR] Restricting interaction records to datasets: collectri; and resources: any
-[2024-04-11 15:20:27] [TRACE]   [OmnipathR] Filtering evidence columns: positive, negative, directed, undirected; to datasets: collectri; and resources: any
-[2024-04-11 15:21:15] [SUCCESS] [OmnipathR] Downloaded 64958 interactions.
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/interactions?genesymbols=yes&resources=CollecTRI&datasets=tf_mirna&organisms=9606&fields=extra_attrs,evidences,sources,references,curation_effort&license=academic`
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/911416570c2aaa914be32ebf7b85e1eb3d1ff162-1.rds`.
-[2024-04-11 15:21:16] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/interactions?genesymbols=yes&resources=CollecTRI&datasets=tf_mirna&organisms=9606&fields=extra_attrs,evidences,sources,references,curation_effort&license=academic`
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Converting JSON column `extra_attrs` to list.
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Converting JSON column `evidences` to list.
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Restricting interaction records to datasets: tf_mirna; and resources: CollecTRI
-[2024-04-11 15:21:16] [TRACE]   [OmnipathR] Filtering evidence columns: positive, negative, directed, undirected; to datasets: tf_mirna; and resources: CollecTRI
-[2024-04-11 15:21:17] [SUCCESS] [OmnipathR] Downloaded 232 interactions.
-[2024-04-11 15:21:18] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=dorothea&organisms=9606&dorothea_levels=A,B,C,D&fields=evidences,sources,references,curation_effort,dorothea_level&license=academic`
-[2024-04-11 15:21:19] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/2acacccd183a8fe4538b649c1e593e2140fcddf6-1.rds`.
-[2024-04-11 15:21:19] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=dorothea&organisms=9606&dorothea_levels=A,B,C,D&fields=evidences,sources,references,curation_effort,dorothea_level&license=academic`
-[2024-04-11 15:21:19] [TRACE]   [OmnipathR] Converting JSON column `evidences` to list.
-[2024-04-11 15:21:30] [TRACE]   [OmnipathR] Restricting interaction records to datasets: dorothea; and resources: any
-[2024-04-11 15:21:44] [TRACE]   [OmnipathR] Filtering evidence columns: positive, negative, directed, undirected; to datasets: dorothea; and resources: any
-[2024-04-11 15:25:00] [SUCCESS] [OmnipathR] Downloaded 278830 interactions.
-[2024-04-11 15:25:08] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
-[2024-04-11 15:25:08] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:25:08] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
-[2024-04-11 15:25:08] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:25:09] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/annotations?resources=PROGENy&license=academic`
-[2024-04-11 15:25:10] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/3492392585ba05414edfae46801492076437d7e7-1.rds`.
-[2024-04-11 15:25:10] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/annotations?resources=PROGENy&license=academic`
-[2024-04-11 15:25:10] [SUCCESS] [OmnipathR] Loaded 700239 annotation records from cache.
-[2024-04-11 15:25:11] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
-[2024-04-11 15:25:11] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:25:12] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
-[2024-04-11 15:25:12] [TRACE]   [OmnipathR] JSON validation successful: TRUE
-[2024-04-11 15:25:12] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/annotations?resources=SIGNOR&license=academic`
-[2024-04-11 15:25:12] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/5d7471d810dce83117cd972d7cef5e5400db8f76-1.rds`.
-[2024-04-11 15:25:12] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/annotations?resources=SIGNOR&license=academic`
-[2024-04-11 15:25:12] [SUCCESS] [OmnipathR] Loaded 2948 annotation records from cache.
-[2024-04-11 15:25:44] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
-[2024-04-11 15:25:44] [TRACE]   [OmnipathR] JSON validation successful: TRUE
diff --git a/reference/omnipathr-log/omnipathr-20241019-1259.log b/reference/omnipathr-log/omnipathr-20241019-1259.log
new file mode 100644
index 00000000..fc7f8b09
--- /dev/null
+++ b/reference/omnipathr-log/omnipathr-20241019-1259.log
@@ -0,0 +1,61 @@
+[2024-10-19 12:59:28] [INFO]    [OmnipathR] Welcome to OmnipathR!
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Reading JSON from `/github/home/.cache/OmnipathR/cache.json` (encoding: UTF-8).
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 12:59:28] [INFO]    [OmnipathR] Initialized cache: `/github/home/.cache/OmnipathR`.
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/db/db_def.json` (encoding: UTF-8).
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/internal/magic_bytes.json` (encoding: UTF-8).
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/internal/urls.json` (encoding: UTF-8).
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Reading JSON from `/usr/local/lib/R/site-library/OmnipathR/internal/id_types.json` (encoding: UTF-8).
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 12:59:28] [INFO]    [OmnipathR] Loading database `Ensembl and OMA organism names`.
+[2024-10-19 12:59:28] [INFO]    [OmnipathR] Looking up in cache `https://www.ensembl.org/info/about/species.html`: key=7332486db7400730697234bad76ca0c8e4d00799, latest version=1.
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Cache file path: /github/home/.cache/OmnipathR/7332486db7400730697234bad76ca0c8e4d00799-1.html
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Looking up in cache: `https://omabrowser.org/All/oma-species.txt`.
+[2024-10-19 12:59:28] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/30e690cbb55dfc63b5903ab337f34ffc2f4be397-1.rds`.
+[2024-10-19 12:59:28] [INFO]    [OmnipathR] Loaded database `Ensembl and OMA organism names`.
+[2024-10-19 12:59:29] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=collectri&organisms=9606&dorothea_levels=A,B&fields=extra_attrs,evidences,sources,references,curation_effort&loops=yes&license=academic`
+[2024-10-19 12:59:29] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/5e82de18cbd9b5d9237867d70ab653aa2a24da2e-1.rds`.
+[2024-10-19 12:59:29] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=collectri&organisms=9606&dorothea_levels=A,B&fields=extra_attrs,evidences,sources,references,curation_effort&loops=yes&license=academic`
+[2024-10-19 12:59:29] [TRACE]   [OmnipathR] Converting JSON column `extra_attrs` to list.
+[2024-10-19 12:59:30] [TRACE]   [OmnipathR] Converting JSON column `evidences` to list.
+[2024-10-19 12:59:34] [TRACE]   [OmnipathR] Restricting interaction records to datasets: collectri; and resources: any
+[2024-10-19 12:59:37] [TRACE]   [OmnipathR] Filtering evidence columns: positive, negative, directed, undirected; to datasets: collectri; and resources: any; excluding resources: none
+[2024-10-19 13:00:39] [SUCCESS] [OmnipathR] Downloaded 64958 interactions.
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/interactions?genesymbols=yes&resources=CollecTRI&datasets=tf_mirna&organisms=9606&fields=extra_attrs,evidences,sources,references,curation_effort&license=academic`
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/911416570c2aaa914be32ebf7b85e1eb3d1ff162-1.rds`.
+[2024-10-19 13:00:39] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/interactions?genesymbols=yes&resources=CollecTRI&datasets=tf_mirna&organisms=9606&fields=extra_attrs,evidences,sources,references,curation_effort&license=academic`
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] Converting JSON column `extra_attrs` to list.
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] Converting JSON column `evidences` to list.
+[2024-10-19 13:00:39] [TRACE]   [OmnipathR] Restricting interaction records to datasets: tf_mirna; and resources: CollecTRI
+[2024-10-19 13:00:40] [TRACE]   [OmnipathR] Filtering evidence columns: positive, negative, directed, undirected; to datasets: tf_mirna; and resources: CollecTRI; excluding resources: none
+[2024-10-19 13:00:40] [SUCCESS] [OmnipathR] Downloaded 232 interactions.
+[2024-10-19 13:00:41] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=dorothea&organisms=9606&dorothea_levels=A,B,C,D&fields=evidences,sources,references,curation_effort,dorothea_level&license=academic`
+[2024-10-19 13:00:42] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/2acacccd183a8fe4538b649c1e593e2140fcddf6-1.rds`.
+[2024-10-19 13:00:42] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/interactions?genesymbols=yes&datasets=dorothea&organisms=9606&dorothea_levels=A,B,C,D&fields=evidences,sources,references,curation_effort,dorothea_level&license=academic`
+[2024-10-19 13:00:42] [TRACE]   [OmnipathR] Converting JSON column `evidences` to list.
+[2024-10-19 13:00:53] [TRACE]   [OmnipathR] Restricting interaction records to datasets: dorothea; and resources: any
+[2024-10-19 13:01:06] [TRACE]   [OmnipathR] Filtering evidence columns: positive, negative, directed, undirected; to datasets: dorothea; and resources: any; excluding resources: none
+[2024-10-19 13:05:19] [SUCCESS] [OmnipathR] Downloaded 278830 interactions.
+[2024-10-19 13:05:26] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
+[2024-10-19 13:05:26] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 13:05:27] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
+[2024-10-19 13:05:27] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 13:05:27] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/annotations?resources=PROGENy&license=academic`
+[2024-10-19 13:05:28] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/3492392585ba05414edfae46801492076437d7e7-1.rds`.
+[2024-10-19 13:05:28] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/annotations?resources=PROGENy&license=academic`
+[2024-10-19 13:05:28] [SUCCESS] [OmnipathR] Loaded 700239 annotation records from cache.
+[2024-10-19 13:05:30] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
+[2024-10-19 13:05:30] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 13:05:31] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
+[2024-10-19 13:05:31] [TRACE]   [OmnipathR] JSON validation successful: TRUE
+[2024-10-19 13:05:31] [TRACE]   [OmnipathR] Looking up in cache: `https://omnipathdb.org/annotations?resources=SIGNOR&license=academic`
+[2024-10-19 13:05:31] [TRACE]   [OmnipathR] Loaded data from RDS `/github/home/.cache/OmnipathR/5d7471d810dce83117cd972d7cef5e5400db8f76-1.rds`.
+[2024-10-19 13:05:31] [INFO]    [OmnipathR] Loaded from cache: `https://omnipathdb.org/annotations?resources=SIGNOR&license=academic`
+[2024-10-19 13:05:31] [SUCCESS] [OmnipathR] Loaded 2948 annotation records from cache.
+[2024-10-19 13:06:02] [TRACE]   [OmnipathR] Reading JSON from `https://omnipathdb.org/resources` (encoding: UTF-8).
+[2024-10-19 13:06:02] [TRACE]   [OmnipathR] JSON validation successful: TRUE
diff --git a/reference/pipe.html b/reference/pipe.html
index 2d02aae4..0eb15da7 100644
--- a/reference/pipe.html
+++ b/reference/pipe.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="See magrittr::%&amp;gt;% for details."><title>Pipe operator — %&gt;% • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pipe operator — %&gt;%"><meta property="og:description" content="See magrittr::%&amp;gt;% for details."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Pipe operator — %&gt;% • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pipe operator — %&gt;%"><meta name="description" content="See magrittr::%&amp;gt;% for details."><meta property="og:description" content="See magrittr::%&amp;gt;% for details."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-<li class="nav-item">
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-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Pipe operator</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-pipe.R" class="external-link"><code>R/utils-pipe.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-pipe.R" class="external-link"><code>R/utils-pipe.R</code></a></small>
       <div class="d-none name"><code>pipe.Rd</code></div>
     </div>
 
@@ -86,9 +57,7 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Pipe an object forward into a function or call expression.</p>
+    <p>Pipe an object forward into a function or call expression.</p>
     </div>
 
     <div class="section level2">
@@ -97,23 +66,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 6</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/pivot_wider_profile.html b/reference/pivot_wider_profile.html
index 236a06b2..8e36d56f 100644
--- a/reference/pivot_wider_profile.html
+++ b/reference/pivot_wider_profile.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Generates a kind of table where the rows come from id_cols,
-the columns from names_from and the values from values_from."><title>Pivot a data frame to wider and convert it to matrix — pivot_wider_profile • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pivot a data frame to wider and convert it to matrix — pivot_wider_profile"><meta property="og:description" content="Generates a kind of table where the rows come from id_cols,
-the columns from names_from and the values from values_from."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Pivot a data frame to wider and convert it to matrix — pivot_wider_profile • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Pivot a data frame to wider and convert it to matrix — pivot_wider_profile"><meta name="description" content="Generates a kind of table where the rows come from id_cols,
+the columns from names_from and the values from values_from."><meta property="og:description" content="Generates a kind of table where the rows come from id_cols,
+the columns from names_from and the values from values_from."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -12,68 +9,42 @@
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 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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-  <a class="nav-link" href="../news/index.html">Changelog</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Pivot a data frame to wider and convert it to matrix</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-profiles.R" class="external-link"><code>R/utils-profiles.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-profiles.R" class="external-link"><code>R/utils-profiles.R</code></a></small>
       <div class="d-none name"><code>pivot_wider_profile.Rd</code></div>
     </div>
 
@@ -98,11 +69,13 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
+
+
+<dl><dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
 <dd><p>A data frame to pivot.</p></dd>
 
 
-<dt>id_cols</dt>
+<dt id="arg-id-cols">id_cols<a class="anchor" aria-label="anchor" href="#arg-id-cols"></a></dt>
 <dd><p>&lt;<code><a href="https://tidyr.tidyverse.org/reference/tidyr_tidy_select.html" class="external-link">tidy-select</a></code>&gt; A set of columns that
 uniquely identify each observation. Typically used when you have
 redundant variables, i.e. variables whose values are perfectly correlated
@@ -113,7 +86,7 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <code>names_from</code> and <code>values_from</code>.</p></dd>
 
 
-<dt>names_from, values_from</dt>
+<dt id="arg-names-from-values-from">names_from, values_from<a class="anchor" aria-label="anchor" href="#arg-names-from-values-from"></a></dt>
 <dd><p>&lt;<code><a href="https://tidyr.tidyverse.org/reference/tidyr_tidy_select.html" class="external-link">tidy-select</a></code>&gt; A pair of
 arguments describing which column (or columns) to get the name of the
 output column (<code>names_from</code>), and which column (or columns) to get the
@@ -122,32 +95,30 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 front of the output column.</p></dd>
 
 
-<dt>values_fill</dt>
+<dt id="arg-values-fill">values_fill<a class="anchor" aria-label="anchor" href="#arg-values-fill"></a></dt>
 <dd><p>Optionally, a (scalar) value that specifies what each
 <code>value</code> should be filled in with when missing.</p>
 <p>This can be a named list if you want to apply different fill values to
 different value columns.</p></dd>
 
 
-<dt>to_matrix</dt>
+<dt id="arg-to-matrix">to_matrix<a class="anchor" aria-label="anchor" href="#arg-to-matrix"></a></dt>
 <dd><p>Logical value indicating if the result should be a matrix.
 Parameter is ignored in case <code>sparse</code> is <code>TRUE</code>.</p></dd>
 
 
-<dt>to_sparse</dt>
+<dt id="arg-to-sparse">to_sparse<a class="anchor" aria-label="anchor" href="#arg-to-sparse"></a></dt>
 <dd><p>Logical value indicating whether the resulting matrix
 should be sparse or not.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Additional arguments passed on to methods.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>"widened" data; it is increasing the number of columns and
+    <p>"widened" data; it is increasing the number of columns and
 decreasing the number of rows.</p>
     </div>
     <div class="section level2">
@@ -158,7 +129,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
 
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># \dontrun{</span></span></span>
 <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></span><span class="op">(</span></span></span>
 <span class="r-in"><span>    tf <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"tf_1"</span>, <span class="st">"tf_1"</span>, <span class="st">"tf_2"</span>, <span class="st">"tf_2"</span><span class="op">)</span>,</span></span>
 <span class="r-in"><span>    gene <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"gene_1"</span>, <span class="st">"gene_2"</span>, <span class="st">"gene_1"</span>, <span class="st">"gene_2"</span><span class="op">)</span>,</span></span>
@@ -189,26 +160,26 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span>    values_from <span class="op">=</span> <span class="va">mor</span>,</span></span>
 <span class="r-in"><span>    to_sparse <span class="op">=</span> <span class="cn">TRUE</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
+<span class="r-in"><span><span class="op">}</span> <span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
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diff --git a/reference/quo_is_missing.html b/reference/quo_is_missing.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/quo_is_missing.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://saezlab.github.io/decoupleR/reference/tidyeval.html">
+  </head>
+</html>
+
diff --git a/reference/quo_is_null.html b/reference/quo_is_null.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/quo_is_null.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://saezlab.github.io/decoupleR/reference/tidyeval.html">
+  </head>
+</html>
+
diff --git a/reference/randomize_matrix.html b/reference/randomize_matrix.html
index bcceab94..30b40891 100644
--- a/reference/randomize_matrix.html
+++ b/reference/randomize_matrix.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Utility function used in functions that require permutations of the
-expression matrix"><title>Randomize matrix — randomize_matrix • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Randomize matrix — randomize_matrix"><meta property="og:description" content="Utility function used in functions that require permutations of the
-expression matrix"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Randomize matrix — randomize_matrix • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Randomize matrix — randomize_matrix"><meta name="description" content="Utility function used in functions that require permutations of the
+expression matrix"><meta property="og:description" content="Utility function used in functions that require permutations of the
+expression matrix"><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
   window.dataLayer = window.dataLayer || [];
   function gtag(){dataLayer.push(arguments);}
   gtag('js', new Date());
@@ -12,68 +9,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
 
     <div id="navbar" class="collapse navbar-collapse ms-3">
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-  <a class="nav-link" href="../articles/decoupleR.html">Get started</a>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">Reference</a>
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Randomize matrix</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-randomize-matrix.R" class="external-link"><code>R/utils-randomize-matrix.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-randomize-matrix.R" class="external-link"><code>R/utils-randomize-matrix.R</code></a></small>
       <div class="d-none name"><code>randomize_matrix.Rd</code></div>
     </div>
 
@@ -89,24 +60,24 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to randomize.</p></dd>
 
 
-<dt>randomize_type</dt>
+<dt id="arg-randomize-type">randomize_type<a class="anchor" aria-label="anchor" href="#arg-randomize-type"></a></dt>
 <dd><p>How to randomize.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Randomized matrix</p>
+    <p>Randomized matrix</p>
     </div>
 
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># \dontrun{</span></span></span>
 <span class="r-in"><span><span class="va">mat</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">9</span><span class="op">)</span>, ncol <span class="op">=</span> <span class="fl">3</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">mat</span></span></span>
 <span class="r-in"><span></span></span>
@@ -115,26 +86,26 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">42</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu">randomize_matrix</span><span class="op">(</span><span class="va">mat</span>, randomize_type <span class="op">=</span> <span class="st">"cols_independently"</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
+<span class="r-in"><span><span class="op">}</span> <span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/rename_net.html b/reference/rename_net.html
index 2ea5ddf6..584e65af 100644
--- a/reference/rename_net.html
+++ b/reference/rename_net.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Renames a given network to these column names: .source, .target, .mor, If
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+.mor is not provided, then the function sets them to default values."><meta property="og:description" content="Renames a given network to these column names: .source, .target, .mor, If
+.mor is not provided, then the function sets them to default values."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Rename network</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-dataset-converters.R" class="external-link"><code>R/utils-dataset-converters.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-dataset-converters.R" class="external-link"><code>R/utils-dataset-converters.R</code></a></small>
       <div class="d-none name"><code>rename_net.Rd</code></div>
     </div>
 
@@ -96,27 +67,29 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>network</dt>
+
+
+<dl><dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>def_mor</dt>
+<dt id="arg-def-mor">def_mor<a class="anchor" aria-label="anchor" href="#arg-def-mor"></a></dt>
 <dd><p>Default value for .mor when not provided.</p></dd>
 
 </dl></div>
@@ -142,23 +115,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> T3     G11      1            1</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/run_aucell.html b/reference/run_aucell.html
index 40f52e18..eaec9049 100644
--- a/reference/run_aucell.html
+++ b/reference/run_aucell.html
@@ -1,8 +1,5 @@
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@@ -10,68 +7,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
-    
+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
 
     <div id="navbar" class="collapse navbar-collapse ms-3">
-      <ul class="navbar-nav me-auto"><li class="nav-item">
-  <a class="nav-link" href="../articles/decoupleR.html">Get started</a>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">Reference</a>
-</li>
+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="github">
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-  <a class="external-link nav-link" href="https://twitter.com/saezlab">
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-  <a class="external-link nav-link" href="https://www.saezlab.org">
-    <span class="fas fa fas fa-university"></span>
-     
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-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>AUCell</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-aucell.R" class="external-link"><code>R/statistic-aucell.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-aucell.R" class="external-link"><code>R/statistic-aucell.R</code></a></small>
       <div class="d-none name"><code>run_aucell.Rd</code></div>
     </div>
 
@@ -95,39 +66,41 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>aucMaxRank</dt>
+<dt id="arg-aucmaxrank">aucMaxRank<a class="anchor" aria-label="anchor" href="#arg-aucmaxrank"></a></dt>
 <dd><p>Threshold to calculate the AUC.</p></dd>
 
 
-<dt>nproc</dt>
+<dt id="arg-nproc">nproc<a class="anchor" aria-label="anchor" href="#arg-nproc"></a></dt>
 <dd><p>Number of cores to use for computation.</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
@@ -146,7 +119,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
 <code><a href="run_gsva.html">run_gsva</a>()</code>,
@@ -184,23 +157,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/run_consensus.html b/reference/run_consensus.html
index 7d2711b7..3476cccf 100644
--- a/reference/run_consensus.html
+++ b/reference/run_consensus.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Function to generate a consensus score between methods from the
-result of the decouple function."><title>Consensus score between methods — run_consensus • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Consensus score between methods — run_consensus"><meta property="og:description" content="Function to generate a consensus score between methods from the
-result of the decouple function."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Consensus score between methods — run_consensus • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Consensus score between methods — run_consensus"><meta name="description" content="Function to generate a consensus score between methods from the
+result of the decouple function."><meta property="og:description" content="Function to generate a consensus score between methods from the
+result of the decouple function."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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   function gtag(){dataLayer.push(arguments);}
   gtag('js', new Date());
@@ -12,68 +9,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
-    
+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
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     <div id="navbar" class="collapse navbar-collapse ms-3">
-      <ul class="navbar-nav me-auto"><li class="nav-item">
-  <a class="nav-link" href="../articles/decoupleR.html">Get started</a>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">Reference</a>
-</li>
+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="github">
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-     
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-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://twitter.com/saezlab">
-    <span class="fab fa fab fa-twitter fa-lg"></span>
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-<li class="nav-item">
-  <a class="external-link nav-link" href="https://www.saezlab.org">
-    <span class="fas fa fas fa-university"></span>
-     
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Consensus score between methods</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-consensus.R" class="external-link"><code>R/decoupleR-consensus.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-consensus.R" class="external-link"><code>R/decoupleR-consensus.R</code></a></small>
       <div class="d-none name"><code>run_consensus.Rd</code></div>
     </div>
 
@@ -89,23 +60,23 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>df</dt>
+
+
+<dl><dt id="arg-df">df<a class="anchor" aria-label="anchor" href="#arg-df"></a></dt>
 <dd><p><code>decouple</code> data frame result</p></dd>
 
 
-<dt>include_time</dt>
+<dt id="arg-include-time">include_time<a class="anchor" aria-label="anchor" href="#arg-include-time"></a></dt>
 <dd><p>Should the time per statistic evaluated be informed?</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>Deprecated parameter.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Updated tibble with the computed consensus score between methods</p>
+    <p>Updated tibble with the computed consensus score between methods</p>
     </div>
 
     <div class="section level2">
@@ -144,23 +115,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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     <footer><div class="pkgdown-footer-left">
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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 <div class="pkgdown-footer-right">
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diff --git a/reference/run_fgsea.html b/reference/run_fgsea.html
index 24ec2201..a047a869 100644
--- a/reference/run_fgsea.html
+++ b/reference/run_fgsea.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities using FGSEA."><title>Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea"><meta property="og:description" content="Calculates regulatory activities using FGSEA."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea"><meta name="description" content="Calculates regulatory activities using FGSEA."><meta property="og:description" content="Calculates regulatory activities using FGSEA."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Fast Gene Set Enrichment Analysis (FGSEA)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-fgsea.R" class="external-link"><code>R/statistic-fgsea.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-fgsea.R" class="external-link"><code>R/statistic-fgsea.R</code></a></small>
       <div class="d-none name"><code>run_fgsea.Rd</code></div>
     </div>
 
@@ -96,42 +67,44 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>times</dt>
+<dt id="arg-times">times<a class="anchor" aria-label="anchor" href="#arg-times"></a></dt>
 <dd><p>How many permutations to do?</p></dd>
 
 
-<dt>nproc</dt>
+<dt id="arg-nproc">nproc<a class="anchor" aria-label="anchor" href="#arg-nproc"></a></dt>
 <dd><p>Number of cores to use for computation.</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Arguments passed on to <code><a href="https://rdrr.io/pkg/fgsea/man/fgseaMultilevel.html" class="external-link">fgsea::fgseaMultilevel</a></code></p><dl><dt><code>sampleSize</code></dt>
 <dd><p>The size of a random set of genes which in turn has size = pathwaySize</p></dd>
 
@@ -163,15 +136,13 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
     <dt><code>absEps</code></dt>
 <dd><p>deprecated, use `eps` parameter instead</p></dd>
 
-  
+
 </dl></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -195,7 +166,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_gsva.html">run_gsva</a>()</code>,
@@ -281,23 +252,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 134 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/run_gsva.html b/reference/run_gsva.html
index 1ecb5522..b315f8fb 100644
--- a/reference/run_gsva.html
+++ b/reference/run_gsva.html
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Gene Set Variation Analysis (GSVA)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-gsva.R" class="external-link"><code>R/statistic-gsva.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-gsva.R" class="external-link"><code>R/statistic-gsva.R</code></a></small>
       <div class="d-none name"><code>run_gsva.Rd</code></div>
     </div>
 
@@ -96,46 +67,48 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>verbose</dt>
+<dt id="arg-verbose">verbose<a class="anchor" aria-label="anchor" href="#arg-verbose"></a></dt>
 <dd><p>Gives information about each calculation step. Default: FALSE.</p></dd>
 
 
-<dt>method</dt>
+<dt id="arg-method">method<a class="anchor" aria-label="anchor" href="#arg-method"></a></dt>
 <dd><p>Method to employ in the estimation of gene-set enrichment.
 scores per sample. By default this is set to gsva (Hänzelmann et al, 2013).
 Further available methods are "plage", "ssgsea" and "zscore". Read more in
 the manual of <code><a href="https://rdrr.io/pkg/GSVA/man/gsva.html" class="external-link">GSVA::gsva</a></code>.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.
 Must be greater than 0.</p></dd>
 
 
-<dt>maxsize</dt>
+<dt id="arg-maxsize">maxsize<a class="anchor" aria-label="anchor" href="#arg-maxsize"></a></dt>
 <dd><p>Integer indicating the maximum number of targets per source.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Arguments passed on to <code><a href="https://rdrr.io/pkg/GSVA/man/gsvaParam-class.html" class="external-link">GSVA::gsvaParam</a></code>, <code><a href="https://rdrr.io/pkg/GSVA/man/ssgseaParam-class.html" class="external-link">GSVA::ssgseaParam</a></code></p><dl><dt><code>assay</code></dt>
 <dd><p>The name of the assay to use in case <code>exprData</code> is a multi-assay
 container, otherwise ignored.  By default, the first assay is used.</p></dd>
@@ -191,15 +164,13 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 between the minimum and the maximum, as described in their paper. Otherwise
 this last normalization step is skipped.</p></dd>
 
-  
+
 </dl></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -219,7 +190,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -257,23 +228,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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diff --git a/reference/run_mdt.html b/reference/run_mdt.html
index 809c764e..9ac457cd 100644
--- a/reference/run_mdt.html
+++ b/reference/run_mdt.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Multivariate Decision Trees (MDT)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-mdt.R" class="external-link"><code>R/statistic-mdt.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-mdt.R" class="external-link"><code>R/statistic-mdt.R</code></a></small>
       <div class="d-none name"><code>run_mdt.Rd</code></div>
     </div>
 
@@ -101,74 +72,74 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Deprecated parameter.</p></dd>
 
 
-<dt>center</dt>
+<dt id="arg-center">center<a class="anchor" aria-label="anchor" href="#arg-center"></a></dt>
 <dd><p>Logical value indicating if <code>mat</code> must be centered by
 <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>.</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>Should missing values (including NaN) be omitted from the
 calculations of <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>?</p></dd>
 
 
-<dt>trees</dt>
+<dt id="arg-trees">trees<a class="anchor" aria-label="anchor" href="#arg-trees"></a></dt>
 <dd><p>An integer for the number of trees contained in the ensemble.</p></dd>
 
 
-<dt>min_n</dt>
+<dt id="arg-min-n">min_n<a class="anchor" aria-label="anchor" href="#arg-min-n"></a></dt>
 <dd><p>An integer for the minimum number of data points in a node that
 are required for the node to be split further.</p></dd>
 
 
-<dt>nproc</dt>
+<dt id="arg-nproc">nproc<a class="anchor" aria-label="anchor" href="#arg-nproc"></a></dt>
 <dd><p>Number of cores to use for computation.</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -184,7 +155,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -222,23 +193,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/run_mlm.html b/reference/run_mlm.html
index b45b39c5..faedc15e 100644
--- a/reference/run_mlm.html
+++ b/reference/run_mlm.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities using MLM."><title>Multivariate Linear Model (MLM) — run_mlm • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Multivariate Linear Model (MLM) — run_mlm"><meta property="og:description" content="Calculates regulatory activities using MLM."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Multivariate Linear Model (MLM) — run_mlm • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Multivariate Linear Model (MLM) — run_mlm"><meta name="description" content="Calculates regulatory activities using MLM."><meta property="og:description" content="Calculates regulatory activities using MLM."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="github">
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-<li class="nav-item">
-  <a class="external-link nav-link" href="https://twitter.com/saezlab">
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-    <span class="fas fa fas fa-university"></span>
-     
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-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Multivariate Linear Model (MLM)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-mlm.R" class="external-link"><code>R/statistic-mlm.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-mlm.R" class="external-link"><code>R/statistic-mlm.R</code></a></small>
       <div class="d-none name"><code>run_mlm.Rd</code></div>
     </div>
 
@@ -97,56 +68,56 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Deprecated parameter.</p></dd>
 
 
-<dt>center</dt>
+<dt id="arg-center">center<a class="anchor" aria-label="anchor" href="#arg-center"></a></dt>
 <dd><p>Logical value indicating if <code>mat</code> must be centered by
 <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>.</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>Should missing values (including NaN) be omitted from the
 calculations of <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>?</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -162,7 +133,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -200,23 +171,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/run_ora.html b/reference/run_ora.html
index 57a9c478..d6c1c489 100644
--- a/reference/run_ora.html
+++ b/reference/run_ora.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities using ORA."><title>Over Representation Analysis (ORA) — run_ora • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Over Representation Analysis (ORA) — run_ora"><meta property="og:description" content="Calculates regulatory activities using ORA."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Over Representation Analysis (ORA) — run_ora • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Over Representation Analysis (ORA) — run_ora"><meta name="description" content="Calculates regulatory activities using ORA."><meta property="og:description" content="Calculates regulatory activities using ORA."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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   function gtag(){dataLayer.push(arguments);}
   gtag('js', new Date());
@@ -10,68 +7,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
 
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-  <a class="nav-link" href="../articles/decoupleR.html">Get started</a>
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
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-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
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-    <span class="fas fa fas fa-university"></span>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Over Representation Analysis (ORA)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-ora.R" class="external-link"><code>R/statistic-ora.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-ora.R" class="external-link"><code>R/statistic-ora.R</code></a></small>
       <div class="d-none name"><code>run_ora.Rd</code></div>
     </div>
 
@@ -98,56 +69,58 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>n_up</dt>
+<dt id="arg-n-up">n_up<a class="anchor" aria-label="anchor" href="#arg-n-up"></a></dt>
 <dd><p>Integer indicating the number of top targets to slice from mat.</p></dd>
 
 
-<dt>n_bottom</dt>
+<dt id="arg-n-bottom">n_bottom<a class="anchor" aria-label="anchor" href="#arg-n-bottom"></a></dt>
 <dd><p>Integer indicating the number of bottom targets to slice from
 mat.</p></dd>
 
 
-<dt>n_background</dt>
+<dt id="arg-n-background">n_background<a class="anchor" aria-label="anchor" href="#arg-n-background"></a></dt>
 <dd><p>Integer indicating the background size of the sliced
 targets. If not specified the number of background targets is determined by
 the total number of unique targets in the union of <code>mat</code> and <code>network</code>.</p></dd>
 
 
-<dt>with_ties</dt>
+<dt id="arg-with-ties">with_ties<a class="anchor" aria-label="anchor" href="#arg-with-ties"></a></dt>
 <dd><p>Should ties be kept together? The default, <code>TRUE</code>,
 may return more rows than you request. Use <code>FALSE</code> to ignore ties,
 and return the first <code>n</code> rows.</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Arguments passed on to <code><a href="https://rdrr.io/r/stats/fisher.test.html" class="external-link">stats::fisher.test</a></code></p><dl><dt><code>workspace</code></dt>
 <dd><p>an integer specifying the size of the workspace
     used in the network algorithm.  In units of 4 bytes.  Only used for
@@ -204,15 +177,13 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <dd><p>an integer specifying the number of replicates used in the
     Monte Carlo test.</p></dd>
 
-  
+
 </dl></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -231,7 +202,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -269,23 +240,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
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   </body></html>
 
diff --git a/reference/run_udt.html b/reference/run_udt.html
index b97be4d0..cec0de16 100644
--- a/reference/run_udt.html
+++ b/reference/run_udt.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities by using UDT."><title>Univariate Decision Tree (UDT) — run_udt • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Univariate Decision Tree (UDT) — run_udt"><meta property="og:description" content="Calculates regulatory activities by using UDT."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Univariate Decision Tree (UDT) — run_udt • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Univariate Decision Tree (UDT) — run_udt"><meta name="description" content="Calculates regulatory activities by using UDT."><meta property="og:description" content="Calculates regulatory activities by using UDT."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -10,68 +7,42 @@
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Univariate Decision Tree (UDT)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-udt.R" class="external-link"><code>R/statistic-udt.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-udt.R" class="external-link"><code>R/statistic-udt.R</code></a></small>
       <div class="d-none name"><code>run_udt.Rd</code></div>
     </div>
 
@@ -99,66 +70,66 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Deprecated parameter.</p></dd>
 
 
-<dt>center</dt>
+<dt id="arg-center">center<a class="anchor" aria-label="anchor" href="#arg-center"></a></dt>
 <dd><p>Logical value indicating if <code>mat</code> must be centered by
 <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>.</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>Should missing values (including NaN) be omitted from the
 calculations of <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>?</p></dd>
 
 
-<dt>min_n</dt>
+<dt id="arg-min-n">min_n<a class="anchor" aria-label="anchor" href="#arg-min-n"></a></dt>
 <dd><p>An integer for the minimum number of data points in a node that
 are required for the node to be split further.</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -174,7 +145,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -212,23 +183,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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 <div class="pkgdown-footer-right">
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/run_ulm.html b/reference/run_ulm.html
index 44bbf181..c32fa050 100644
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+++ b/reference/run_ulm.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Univariate Linear Model (ULM) — run_ulm • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Univariate Linear Model (ULM) — run_ulm"><meta name="description" content="Calculates regulatory activities using ULM."><meta property="og:description" content="Calculates regulatory activities using ULM."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
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+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Univariate Linear Model (ULM)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-ulm.R" class="external-link"><code>R/statistic-ulm.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-ulm.R" class="external-link"><code>R/statistic-ulm.R</code></a></small>
       <div class="d-none name"><code>run_ulm.Rd</code></div>
     </div>
 
@@ -97,56 +68,56 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Deprecated parameter.</p></dd>
 
 
-<dt>center</dt>
+<dt id="arg-center">center<a class="anchor" aria-label="anchor" href="#arg-center"></a></dt>
 <dd><p>Logical value indicating if <code>mat</code> must be centered by
 <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>.</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>Should missing values (including NaN) be omitted from the
 calculations of <code><a href="https://rdrr.io/r/base/colSums.html" class="external-link">base::rowMeans()</a></code>?</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -162,7 +133,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -200,23 +171,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/run_viper.html b/reference/run_viper.html
index bd881bee..c09dd308 100644
--- a/reference/run_viper.html
+++ b/reference/run_viper.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities using VIPER."><title>Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper"><meta property="og:description" content="Calculates regulatory activities using VIPER."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-viper.R" class="external-link"><code>R/statistic-viper.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-viper.R" class="external-link"><code>R/statistic-viper.R</code></a></small>
       <div class="d-none name"><code>run_viper.Rd</code></div>
     </div>
 
@@ -98,53 +69,55 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>verbose</dt>
+<dt id="arg-verbose">verbose<a class="anchor" aria-label="anchor" href="#arg-verbose"></a></dt>
 <dd><p>Logical, whether progression messages should be printed in
 the terminal.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 
-<dt>pleiotropy</dt>
+<dt id="arg-pleiotropy">pleiotropy<a class="anchor" aria-label="anchor" href="#arg-pleiotropy"></a></dt>
 <dd><p>Logical, whether correction for pleiotropic regulation
 should be performed.</p></dd>
 
 
-<dt>eset.filter</dt>
+<dt id="arg-eset-filter">eset.filter<a class="anchor" aria-label="anchor" href="#arg-eset-filter"></a></dt>
 <dd><p>Logical, whether the dataset should be limited only to
 the genes represented in the interactome.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>Arguments passed on to <code><a href="https://rdrr.io/pkg/viper/man/viper.html" class="external-link">viper::viper</a></code></p><dl><dt><code>dnull</code></dt>
 <dd><p>Numeric matrix for the null model, usually generated by <code>nullTtest</code></p></dd>
 
@@ -166,15 +139,13 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
     <dt><code>cores</code></dt>
 <dd><p>Integer indicating the number of cores to use (only 1 in Windows-based systems)</p></dd>
 
-  
+
 </dl></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -192,7 +163,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -230,23 +201,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 62 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/run_wmean.html b/reference/run_wmean.html
index 77b07cae..0ec11fea 100644
--- a/reference/run_wmean.html
+++ b/reference/run_wmean.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities using WMEAN."><title>Weighted Mean (WMEAN) — run_wmean • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Weighted Mean (WMEAN) — run_wmean"><meta property="og:description" content="Calculates regulatory activities using WMEAN."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Weighted Mean (WMEAN) — run_wmean • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Weighted Mean (WMEAN) — run_wmean"><meta name="description" content="Calculates regulatory activities using WMEAN."><meta property="og:description" content="Calculates regulatory activities using WMEAN."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
-    <a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a>
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-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">Changelog</a>
-</li>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Weighted Mean (WMEAN)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-wmean.R" class="external-link"><code>R/statistic-wmean.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-wmean.R" class="external-link"><code>R/statistic-wmean.R</code></a></small>
       <div class="d-none name"><code>run_wmean.Rd</code></div>
     </div>
 
@@ -98,59 +69,59 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>times</dt>
+<dt id="arg-times">times<a class="anchor" aria-label="anchor" href="#arg-times"></a></dt>
 <dd><p>How many permutations to do?</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Should the matrices used for the calculation be sparse?</p></dd>
 
 
-<dt>randomize_type</dt>
+<dt id="arg-randomize-type">randomize_type<a class="anchor" aria-label="anchor" href="#arg-randomize-type"></a></dt>
 <dd><p>How to randomize the expression matrix.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -168,7 +139,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -206,23 +177,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 206 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
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   </body></html>
 
diff --git a/reference/run_wsum.html b/reference/run_wsum.html
index 28e288f3..11849f6a 100644
--- a/reference/run_wsum.html
+++ b/reference/run_wsum.html
@@ -1,8 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculates regulatory activities using WSUM."><title>Weighted Sum (WSUM) — run_wsum • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Weighted Sum (WSUM) — run_wsum"><meta property="og:description" content="Calculates regulatory activities using WSUM."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Weighted Sum (WSUM) — run_wsum • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Weighted Sum (WSUM) — run_wsum"><meta name="description" content="Calculates regulatory activities using WSUM."><meta property="og:description" content="Calculates regulatory activities using WSUM."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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   gtag('js', new Date());
@@ -10,68 +7,42 @@
   gtag('config', 'UA-119440867-11');
 </script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
     <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">2.9.7</small>
 
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+
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+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../articles/decoupleR.html">Get started</a></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
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-    <a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a>
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-    <a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://twitter.com/saezlab"><span class="fa fab fa-twitter fa-lg"></span></a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://www.saezlab.org"><span class="fa fas fa-university"></span></a></li>
       </ul></div>
 
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Weighted Sum (WSUM)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/statistic-wsum.R" class="external-link"><code>R/statistic-wsum.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/statistic-wsum.R" class="external-link"><code>R/statistic-wsum.R</code></a></small>
       <div class="d-none name"><code>run_wsum.Rd</code></div>
     </div>
 
@@ -98,59 +69,59 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mat</dt>
+
+
+<dl><dt id="arg-mat">mat<a class="anchor" aria-label="anchor" href="#arg-mat"></a></dt>
 <dd><p>Matrix to evaluate (e.g. expression matrix).
 Target nodes in rows and conditions in columns.
 <code>rownames(mat)</code> must have at least one intersection with the elements
 in <code>network</code> <code>.target</code> column.</p></dd>
 
 
-<dt>network</dt>
+<dt id="arg-network">network<a class="anchor" aria-label="anchor" href="#arg-network"></a></dt>
 <dd><p>Tibble or dataframe with edges and it's associated metadata.</p></dd>
 
 
-<dt>.source</dt>
+<dt id="arg--source">.source<a class="anchor" aria-label="anchor" href="#arg--source"></a></dt>
 <dd><p>Column with source nodes.</p></dd>
 
 
-<dt>.target</dt>
+<dt id="arg--target">.target<a class="anchor" aria-label="anchor" href="#arg--target"></a></dt>
 <dd><p>Column with target nodes.</p></dd>
 
 
-<dt>.mor</dt>
+<dt id="arg--mor">.mor<a class="anchor" aria-label="anchor" href="#arg--mor"></a></dt>
 <dd><p>Column with edge mode of regulation (i.e. mor).</p></dd>
 
 
-<dt>.likelihood</dt>
+<dt id="arg--likelihood">.likelihood<a class="anchor" aria-label="anchor" href="#arg--likelihood"></a></dt>
 <dd><p>Deprecated argument. Now it will always be set to 1.</p></dd>
 
 
-<dt>times</dt>
+<dt id="arg-times">times<a class="anchor" aria-label="anchor" href="#arg-times"></a></dt>
 <dd><p>How many permutations to do?</p></dd>
 
 
-<dt>seed</dt>
+<dt id="arg-seed">seed<a class="anchor" aria-label="anchor" href="#arg-seed"></a></dt>
 <dd><p>A single value, interpreted as an integer, or NULL for random
 number generation.</p></dd>
 
 
-<dt>sparse</dt>
+<dt id="arg-sparse">sparse<a class="anchor" aria-label="anchor" href="#arg-sparse"></a></dt>
 <dd><p>Should the matrices used for the calculation be sparse?</p></dd>
 
 
-<dt>randomize_type</dt>
+<dt id="arg-randomize-type">randomize_type<a class="anchor" aria-label="anchor" href="#arg-randomize-type"></a></dt>
 <dd><p>How to randomize the expression matrix.</p></dd>
 
 
-<dt>minsize</dt>
+<dt id="arg-minsize">minsize<a class="anchor" aria-label="anchor" href="#arg-minsize"></a></dt>
 <dd><p>Integer indicating the minimum number of targets per source.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A long format tibble of the enrichment scores for each source
+    <p>A long format tibble of the enrichment scores for each source
 across the samples. Resulting tibble contains the following columns:</p><ol><li><p><code>statistic</code>: Indicates which method is associated with which score.</p></li>
 <li><p><code>source</code>: Source nodes of <code>network</code>.</p></li>
 <li><p><code>condition</code>: Condition representing each column of <code>mat</code>.</p></li>
@@ -168,7 +139,7 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>Other decoupleR statistics: 
+    <div class="dont-index"><p>Other decoupleR statistics:
 <code><a href="decouple.html">decouple</a>()</code>,
 <code><a href="run_aucell.html">run_aucell</a>()</code>,
 <code><a href="run_fgsea.html">run_fgsea</a>()</code>,
@@ -206,23 +177,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 206 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
 </div>
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/show_methods.html b/reference/show_methods.html
index a5798167..3e72b61b 100644
--- a/reference/show_methods.html
+++ b/reference/show_methods.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prints the methods available in decoupleR. The first column correspond to
-the function name in decoupleR and the second to the method's full name."><title>Show methods — show_methods • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Show methods — show_methods"><meta property="og:description" content="Prints the methods available in decoupleR. The first column correspond to
-the function name in decoupleR and the second to the method's full name."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-<![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Show methods — show_methods • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Show methods — show_methods"><meta name="description" content="Prints the methods available in decoupleR. The first column correspond to
+the function name in decoupleR and the second to the method's full name."><meta property="og:description" content="Prints the methods available in decoupleR. The first column correspond to
+the function name in decoupleR and the second to the method's full name."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -12,68 +9,42 @@
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     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
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     <a class="navbar-brand me-2" href="../index.html">decoupleR</a>
 
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+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Show methods</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/decoupleR-pre.R" class="external-link"><code>R/decoupleR-pre.R</code></a></small>
       <div class="d-none name"><code>show_methods.Rd</code></div>
     </div>
 
@@ -108,23 +79,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">12</span> run_wsum      Weighted Sum (WSUM)                                            </span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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     <footer><div class="pkgdown-footer-left">
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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-  
 
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+
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diff --git a/reference/show_resources.html b/reference/show_resources.html
index ec1d60f5..7454a79f 100644
--- a/reference/show_resources.html
+++ b/reference/show_resources.html
@@ -1,10 +1,7 @@
 <!DOCTYPE html>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources"><meta name="description" content="Shows available resources in Omnipath. For more information visit the
+official website for Omnipath."><meta property="og:description" content="Shows available resources in Omnipath. For more information visit the
+official website for Omnipath."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-119440867-11"></script><script>
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@@ -12,68 +9,42 @@
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/pw_bk.html">Pathway activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/pw_sc.html">Pathway activity inference from scRNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_bk.html">Transcription factor activity inference in bulk RNA-seq</a></li>
+    <li><a class="dropdown-item" href="../articles/tf_sc.html">Transcription factor activity inference from scRNA-seq</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="external-link nav-link" href="https://github.com/saezlab/decoupleR/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
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+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Shows available resources in Omnipath. For more information visit the official website for <a href="https://omnipathdb.org/" class="external-link">Omnipath</a>.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/HEAD/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/saezlab/decoupleR/blob/master/R/utils-omnipath.R" class="external-link"><code>R/utils-omnipath.R</code></a></small>
       <div class="d-none name"><code>show_resources.Rd</code></div>
     </div>
 
@@ -120,23 +91,23 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> [79] "talklr"              </span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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+  <p>Developed by Pau Badia-i-Mompel, Jesús Vélez-Santiago, Jana Braunger, Celina Geiss, Daniel Dimitrov, Sophia Müller-Dott, Petr Taus, Aurélien Dugourd, Christian H. Holland, Ricardo O. Ramirez Flores, Julio Saez-Rodriguez.</p>
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.8.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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diff --git a/reference/sym.html b/reference/sym.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/sym.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://saezlab.github.io/decoupleR/reference/tidyeval.html">
+  </head>
+</html>
+
diff --git a/reference/syms.html b/reference/syms.html
new file mode 100644
index 00000000..d9caf5f6
--- /dev/null
+++ b/reference/syms.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://saezlab.github.io/decoupleR/reference/tidyeval.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://saezlab.github.io/decoupleR/reference/tidyeval.html">
+  </head>
+</html>
+
diff --git a/reference/tidyeval.html b/reference/tidyeval.html
index 898f6703..edde0d3f 100644
--- a/reference/tidyeval.html
+++ b/reference/tidyeval.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Tidy eval helpers — tidyeval • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Tidy eval helpers — tidyeval"><meta name="description" content="
 
 rlang::sym() creates a symbol from a string and
 syms() creates a list of symbols from a
@@ -31,7 +31,7 @@
 To learn more about tidy eval and how to use these tools, visit
 https://tidyeval.tidyverse.org and the
 Metaprogramming section of
-Advanced R."><title>Tidy eval helpers — tidyeval • decoupleR</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><meta property="og:title" content="Tidy eval helpers — tidyeval"><meta property="og:description" content="
+Advanced R."><meta property="og:description" content="
 
 rlang::sym() creates a symbol from a string and
 syms() creates a list of symbols from a
@@ -63,10 +63,7 @@
 To learn more about tidy eval and how to use these tools, visit
 https://tidyeval.tidyverse.org and the
 Metaprogramming section of
-Advanced R."><meta property="og:image" content="https://saezlab.github.io/decoupleR/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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diff --git a/search.json b/search.json
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-[{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"Introduction","text":"decoupleR R package distributed part Bioconductor project. install package, start R enter: Alternatively, can instead install latest development version GitHub :","code":"install.packages(\"BiocManager\") BiocManager::install(\"decoupleR\") BiocManager::install(\"saezlab/decoupleR\")"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"usage","dir":"Articles","previous_headings":"","what":"Usage","title":"Introduction","text":"decoupleR (Badia--Mompel, Santiago, Braunger, Geiss, Dimitrov, Müller-Dott, Taus, Dugourd, Holland, Flores, Saez-Rodriguez, 2022) contains different statistical methods extract biological activities omics data using prior knowledge. : AUCell: (Aibar, Bravo Gonzalez-Blas, Moerman, Huynh-Thu, Imrichova, Hulselmans, Rambow, Marine, Geurts, Aerts, van den Oord, Kalender Atak, Wouters, Aerts, 2017) Fast GSEA: (Korotkevich, Sukhov, Sergushichev, 2019) GSVA: (H{ä}nzelmann, Castelo, Guinney, 2013) viper: (Alvarez, Shen, Giorgi, Lachmann, Ding, Ye, Califano, 2016) vignette showcase use toy data.","code":""},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"libraries","dir":"Articles","previous_headings":"Usage","what":"Libraries","title":"Introduction","text":"decoupleR can imported :","code":"library(decoupleR)  # Extra libraries library(dplyr) library(pheatmap)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"input-data","dir":"Articles","previous_headings":"Usage","what":"Input data","title":"Introduction","text":"decoupleR needs matrix (mat) molecular readouts (gene expression, logFC, p-values, etc.) network relates target features (genes, proteins, etc.) “source” biological entities (pathways, transcription factors, molecular processes, etc.). methods also require mode regulation (MoR) interaction, defined negative positive weights. get example data-set, run: example consists two small populations samples (S, cols) different gene expression patterns (G, rows):  can see genes seem expressed one group samples vice-versa. Ideally, like capture differences gene programs interpretable biological entities. example summarizing gene expression transcription factor activities. toy data also contains simple net consisting 3 transcription factors (Ts) specific regulation target genes (either positive negative). network can visualized like graph. Green edges positive regulation (activation), red edges negative regulation (inactivation):  According network, first population samples show high activity T1 T3, second one T2.","code":"data <- get_toy_data()  mat <- data$mat head(mat,5)[,1:5] #>           S01       S02       S03        S04      S05 #> G01 9.3709584 9.3888607 9.8951935  8.7844590 8.431446 #> G02 8.5646982 8.2787888 8.4304691  8.8509076 8.655648 #> G03 8.3631284 8.1333213 8.2572694 10.4142076 8.321925 #> G04 8.6328626 8.6359504 9.7631631  8.0361226 8.783839 #> G05 0.4042683 0.2842529 0.4600974  0.2059986 1.575728  network <- data$network network #> # A tibble: 10 × 3 #>    source target   mor #>    <chr>  <chr>  <dbl> #>  1 T1     G01      1   #>  2 T1     G02      1   #>  3 T1     G03      0.7 #>  4 T2     G06      1   #>  5 T2     G07      0.5 #>  6 T2     G08      1   #>  7 T3     G06     -0.5 #>  8 T3     G07     -3   #>  9 T3     G08     -1   #> 10 T3     G11      1 pheatmap(mat, cluster_rows = F, cluster_cols = F)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"methods","dir":"Articles","previous_headings":"Usage","what":"Methods","title":"Introduction","text":"decoupleR contains several methods. check many available, run: method models biological activities different manner, sometimes returning one estimate providing significance estimation. know method returns, please check documentation like ?run_mlm. unified framework, methods shared arguments: mat : input matrix molecular readouts. network : input prior knowledge information relating molecular features biological entities. .source refers biological entities. .target refers molecular features. .mor refers “strength” interaction (available, else 1s used). available methods can model interaction weights. minsize : Minimum target features per biological entity (5 default). less, sources removed. filtering prevents obtaining noisy activities biological entities matching target features matrix. example data-set keep 0 though.","code":"show_methods() #> # A tibble: 12 × 2 #>    Function      Name                                                            #>    <chr>         <chr>                                                           #>  1 run_aucell    AUCell                                                          #>  2 run_consensus Consensus score between methods                                 #>  3 run_fgsea     Fast Gene Set Enrichment Analysis (FGSEA)                       #>  4 run_gsva      Gene Set Variation Analysis (GSVA)                              #>  5 run_mdt       Multivariate Decision Trees (MDT)                               #>  6 run_mlm       Multivariate Linear Model (MLM)                                 #>  7 run_ora       Over Representation Analysis (ORA)                              #>  8 run_udt       Univariate Decision Tree (UDT)                                  #>  9 run_ulm       Univariate Linear Model (ULM)                                   #> 10 run_viper     Virtual Inference of Protein-activity by Enriched Regulon anal… #> 11 run_wmean     Weighted Mean (WMEAN)                                           #> 12 run_wsum      Weighted Sum (WSUM)"},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"individual-methods","dir":"Articles","previous_headings":"Usage > Running methods","what":"Individual methods","title":"Introduction","text":"example, let’s first run Gene Set Enrichment Analysis method (gsea), one well-known statistics: Methods return result data-frame containing: statistic: name statistic. Depending method, can one per method. source: name biological entity. condition: sample name. score: inferred biological activity. p_value: available, significance inferred activity. case gsea, returns simple estimate activities (fgsea), normalized estimate (norm_fgsea) p-values permutations. methods can return different things, example Univariate Linear Model (ulm): case, ulm returns just estimate (ulm) associated p-values. method can return different statistics, recommend check documentation know . Let us plot obtained results, first gsea:  can observe transcription factors T1 T2, obtained activities correctly distinguish two sample populations. T3, hand, second population samples since repressor. mislabeling activities happens gsea model weights inferring biological activities. weights available prior knowledge, definitely recommend using methods take account get better estimates, one example ulm:  Since ulm models weights estimating biological activities, correctly assigns T3 inactive second population samples.","code":"res_gsea <- run_fgsea(mat, network, .source='source', .target='target', nproc=1, minsize = 0) #>   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100% #>  #>   |                                                                              |                                                                      |   0%  |                                   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                                  |  50%  |                                                                              |======================================================================| 100% res_gsea #> # A tibble: 144 × 5 #>    statistic  source condition   score p_value #>    <chr>      <chr>  <chr>       <dbl>   <dbl> #>  1 fgsea      T1     S01         0.889  0.0755 #>  2 norm_fgsea T1     S01         1.24   0.0755 #>  3 fgsea      T2     S01        -0.667  0.548  #>  4 norm_fgsea T2     S01        -1.11   0.548  #>  5 fgsea      T3     S01        -0.75   0.01   #>  6 norm_fgsea T3     S01       Inf      0.01   #>  7 fgsea      T1     S02         0.889  0.0764 #>  8 norm_fgsea T1     S02         1.29   0.0764 #>  9 fgsea      T2     S02         0      0.977  #> 10 norm_fgsea T2     S02         0      0.977  #> # ℹ 134 more rows res_ulm <- run_ulm(mat, network, .source='source', .target='target', .mor='mor', minsize = 0) res_ulm #> # A tibble: 72 × 5 #>    statistic source condition score  p_value #>    <chr>     <chr>  <chr>     <dbl>    <dbl> #>  1 ulm       T1     S01        4.21 0.00180  #>  2 ulm       T1     S02        4.07 0.00224  #>  3 ulm       T1     S03        3.85 0.00319  #>  4 ulm       T1     S04        4.60 0.000979 #>  5 ulm       T1     S05        3.90 0.00298  #>  6 ulm       T1     S06        3.66 0.00442  #>  7 ulm       T1     S07        4.31 0.00153  #>  8 ulm       T1     S08        4.65 0.000902 #>  9 ulm       T1     S09        4.49 0.00117  #> 10 ulm       T1     S10        4.07 0.00225  #> # ℹ 62 more rows # Transform to matrix mat_gsea <- res_gsea %>%   filter(statistic=='fgsea') %>%   pivot_wider_profile(id_cols = source, names_from = condition,                        values_from = score) %>%   as.matrix()  pheatmap(mat_gsea, cluster_rows = F, cluster_cols = F, cellwidth = 15, cellheight = 40) # Transform to matrix mat_ulm <- res_ulm %>%   filter(statistic=='ulm') %>%   pivot_wider_profile(id_cols = source, names_from = condition,                        values_from = score) %>%   as.matrix()  pheatmap(mat_ulm, cluster_rows = F, cluster_cols = F, cellwidth = 15, cellheight = 40)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"multiple-methods","dir":"Articles","previous_headings":"Usage > Running methods","what":"Multiple methods","title":"Introduction","text":"decoupleR also allows run multiple methods time. Moreover, computes consensus score based obtained activities across methods, called consensus. default, deocuple runs top performer methods benchmark (mlm, ulm wsum), estimates consensus score across . Specific arguments specific methods can passed using variable args. information check ?decouple. Let us see result consensus score previous decouple run:  can observe consensus score correctly predicts T1 T3 active first population samples T2 second one.","code":"res_decouple <- decouple(mat,                           network,                           .source='source',                           .target='target',                          minsize = 0) res_decouple #> # A tibble: 432 × 6 #>    run_id statistic source condition   score p_value #>     <dbl> <chr>     <chr>  <chr>       <dbl>   <dbl> #>  1      1 mlm       T1     S01        3.52   0.00781 #>  2      1 mlm       T2     S01       -1.13   0.290   #>  3      1 mlm       T3     S01       -0.247  0.811   #>  4      1 mlm       T1     S02        3.48   0.00831 #>  5      1 mlm       T2     S02       -0.213  0.837   #>  6      1 mlm       T3     S02       -0.353  0.733   #>  7      1 mlm       T1     S03        3.15   0.0135  #>  8      1 mlm       T2     S03       -0.638  0.541   #>  9      1 mlm       T3     S03        0.0749 0.942   #> 10      1 mlm       T1     S04        3.82   0.00512 #> # ℹ 422 more rows # Transform to matrix mat_consensus <- res_decouple %>%   filter(statistic=='consensus') %>%   pivot_wider_profile(id_cols = source, names_from = condition,                        values_from = score) %>%   as.matrix()  pheatmap(mat_consensus, cluster_rows = F, cluster_cols = F, cellwidth = 15, cellheight = 40)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Introduction","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R Under development (unstable) (2024-04-03 r86327) #>  os       Ubuntu 22.04.4 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-04-11 #>  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package      * version date (UTC) lib source #>  backports      1.4.1   2021-12-13 [1] CRAN (R 4.5.0) #>  bibtex         0.5.1   2023-01-26 [1] CRAN (R 4.5.0) #>  BiocManager    1.30.22 2023-08-08 [1] CRAN (R 4.5.0) #>  BiocParallel   1.37.1  2024-03-04 [1] Bioconduc~ #>  BiocStyle    * 2.31.0  2023-10-24 [1] Bioconductor #>  bookdown       0.38    2024-03-04 [1] CRAN (R 4.5.0) #>  bslib          0.7.0   2024-03-29 [1] CRAN (R 4.5.0) #>  cachem         1.0.8   2023-05-01 [1] CRAN (R 4.5.0) #>  cli            3.6.2   2023-12-11 [1] CRAN (R 4.5.0) #>  codetools      0.2-20  2024-03-31 [2] CRAN (R 4.5.0) #>  colorspace     2.1-0   2023-01-23 [1] CRAN (R 4.5.0) #>  cowplot        1.1.3   2024-01-22 [1] CRAN (R 4.5.0) #>  data.table     1.15.4  2024-03-30 [1] CRAN (R 4.5.0) #>  decoupleR    * 2.9.7   2024-04-11 [1] Bioconductor #>  desc           1.4.3   2023-12-10 [1] CRAN (R 4.5.0) #>  digest         0.6.35  2024-03-11 [1] CRAN (R 4.5.0) #>  dplyr        * 1.1.4   2023-11-17 [1] CRAN (R 4.5.0) #>  evaluate       0.23    2023-11-01 [1] CRAN (R 4.5.0) #>  fansi          1.0.6   2023-12-08 [1] CRAN (R 4.5.0) #>  fastmap        1.1.1   2023-02-24 [1] CRAN (R 4.5.0) #>  fastmatch      1.1-4   2023-08-18 [1] CRAN (R 4.5.0) #>  fgsea          1.29.0  2023-10-24 [1] Bioconductor #>  fs             1.6.3   2023-07-20 [1] CRAN (R 4.5.0) #>  generics       0.1.3   2022-07-05 [1] CRAN (R 4.5.0) #>  ggplot2        3.5.0   2024-02-23 [1] CRAN (R 4.5.0) #>  glue           1.7.0   2024-01-09 [1] CRAN (R 4.5.0) #>  gtable         0.3.4   2023-08-21 [1] CRAN (R 4.5.0) #>  highr          0.10    2022-12-22 [1] CRAN (R 4.5.0) #>  htmltools      0.5.8.1 2024-04-04 [1] CRAN (R 4.5.0) #>  htmlwidgets    1.6.4   2023-12-06 [1] CRAN (R 4.5.0) #>  httr           1.4.7   2023-08-15 [1] CRAN (R 4.5.0) #>  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#>  utf8           1.2.4   2023-10-22 [1] CRAN (R 4.5.0) #>  vctrs          0.6.5   2023-12-01 [1] CRAN (R 4.5.0) #>  withr          3.0.0   2024-01-16 [1] CRAN (R 4.5.0) #>  xfun           0.43    2024-03-25 [1] CRAN (R 4.5.0) #>  xml2           1.3.6   2023-12-04 [1] CRAN (R 4.5.0) #>  yaml           2.3.8   2023-12-11 [1] CRAN (R 4.5.0) #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"bibliography","dir":"Articles","previous_headings":"","what":"Bibliography","title":"Introduction","text":"[1] S. Aibar, C. Bravo Gonzalez-Blas, T. Moerman, et al. “SCENIC: Single-Cell Regulatory Network Inference Clustering”. : Nature Methods 14 (2017), pp. 1083-1086. DOI: 10.1038/nmeth.4463. [2] M. J. Alvarez, Y. Shen, F. M. Giorgi, et al. “Functional characterization somatic mutations cancer using network-based inference protein activity”. : Nature genetics 48.8 (2016), pp. 838–47. [3] P. Badia--Mompel, J. V. Santiago, J. Braunger, et al. “decoupleR: ensemble computational methods infer biological activities omics data”. : Bioinformatics Advances (2022). DOI: https://doi.org/10.1093/bioadv/vbac016. [4] S. Hänzelmann, R. Castelo, J. Guinney. “GSVA: gene set variation analysis microarray RNA-Seq data”. : BMC Bioinformatics 14 (2013), p. 7. DOI: 10.1186/1471-2105-14-7. URL: https://doi.org/10.1186/1471-2105-14-7. [5] G. Korotkevich, V. Sukhov, . Sergushichev. “Fast gene set enrichment analysis”. : bioRxiv (2019). DOI: 10.1101/060012. URL: http://biorxiv.org/content/early/2016/06/20/060012.","code":""},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Pathway activity inference in bulk RNA-seq","text":"First, need load relevant packages:","code":"## We load the required packages library(decoupleR) library(dplyr) library(tibble) library(tidyr) library(ggplot2) library(pheatmap) library(ggrepel)"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Pathway activity inference in bulk RNA-seq","text":"used already processed bulk RNA-seq data-set. provide normalized log-transformed counts, experimental design meta-data Differential Expressed Genes (DEGs) obtained using limma. example use limma used DeSeq2, edgeR statistical framework. decoupleR requires gene level statistic perform enrichment analysis agnostic generated. However, recommend use statistics include direction change significance, example t-value obtained limma(t) DeSeq2(stat). edgeR return statistic can create weighting obtained logFC pvalue formula: -log10(pvalue) * logFC. can open data like : data can extract mentioned information. see normalized log-transformed counts: design meta-data: results limma, interested extracting obtained t-value contrast:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"bk_data.rds\")) # Remove NAs and set row names counts <- data$counts %>%   dplyr::mutate_if(~ any(is.na(.x)), ~ if_else(is.na(.x),0,.x)) %>%    column_to_rownames(var = \"gene\") %>%    as.matrix() head(counts) #>          PANC1.WT.Rep1 PANC1.WT.Rep2 PANC1.WT.Rep3 PANC1.FOXA2KO.Rep1 #> NOC2L        10.052588     11.949123     12.057774          12.312291 #> PLEKHN1       7.535115      8.125993      8.714880           8.048196 #> PERM1         6.281242      6.424582      6.589668           6.293285 #> ISG15        10.938252     11.469081     11.425415          11.549986 #> AGRN          6.956335      7.196108      7.522550           7.061549 #> C1orf159      9.546224      9.788721      9.794589           9.850830 #>          PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO.Rep3 #> NOC2L             12.139918          11.494205 #> PLEKHN1            8.290154           8.621239 #> PERM1              6.486136           6.775344 #> ISG15             11.371464          11.178157 #> AGRN               7.485534           7.071555 #> C1orf159           9.988069           9.965357 design <- data$design design #> # A tibble: 6 × 2 #>   sample             condition     #>   <chr>              <chr>         #> 1 PANC1.WT.Rep1      PANC1.WT      #> 2 PANC1.WT.Rep2      PANC1.WT      #> 3 PANC1.WT.Rep3      PANC1.WT      #> 4 PANC1.FOXA2KO.Rep1 PANC1.FOXA2KO #> 5 PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO #> 6 PANC1.FOXA2KO.Rep3 PANC1.FOXA2KO # Extract t-values per gene deg <- data$limma_ttop %>%     select(ID, t) %>%      filter(!is.na(t)) %>%      column_to_rownames(var = \"ID\") %>%     as.matrix() head(deg) #>                  t #> RHBDL2  -12.810588 #> PLEKHH2 -10.794453 #> HEG1     -9.788112 #> CLU      -9.761618 #> FHL1      8.950191 #> RBP4     -8.529074"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"progeny-model","dir":"Articles","previous_headings":"","what":"PROGENy model","title":"Pathway activity inference in bulk RNA-seq","text":"PROGENy comprehensive resource containing curated collection pathways target genes, weights interaction. example use human weights (organisms available) use top 500 responsive genes ranked p-value. brief description pathway: Androgen: involved growth development male reproductive organs. EGFR: regulates growth, survival, migration, apoptosis, proliferation, differentiation mammalian cells Estrogen: promotes growth development female reproductive organs. Hypoxia: promotes angiogenesis metabolic reprogramming O2 levels low. JAK-STAT: involved immunity, cell division, cell death, tumor formation. MAPK: integrates external signals promotes cell growth proliferation. NFkB: regulates immune response, cytokine production cell survival. p53: regulates cell cycle, apoptosis, DNA repair tumor suppression. PI3K: promotes growth proliferation. TGFb: involved development, homeostasis, repair tissues. TNFa: mediates haematopoiesis, immune surveillance, tumour regression protection infection. Trail: induces apoptosis. VEGF: mediates angiogenesis, vascular permeability, cell migration. WNT: regulates organ morphogenesis development tissue repair. access can use decoupleR:","code":"net <- get_progeny(organism = 'human', top = 500) net #> # A tibble: 7,000 × 4 #>    source   target  weight  p_value #>    <chr>    <chr>    <dbl>    <dbl> #>  1 Androgen TMPRSS2  11.5  2.38e-47 #>  2 Androgen NKX3-1   10.6  2.21e-44 #>  3 Androgen MBOAT2   10.5  4.63e-44 #>  4 Androgen KLK2     10.2  1.94e-40 #>  5 Androgen SARG     11.4  2.79e-40 #>  6 Androgen SLC38A4   7.36 1.25e-39 #>  7 Androgen MTMR9     6.13 2.53e-38 #>  8 Androgen ZBTB16   10.6  1.57e-36 #>  9 Androgen KCNN2     9.47 7.71e-36 #> 10 Androgen OPRK1    -5.63 1.11e-35 #> # ℹ 6,990 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"activity-inference-with-multivariate-linear-model-mlm","dir":"Articles","previous_headings":"","what":"Activity inference with Multivariate Linear Model (MLM)","title":"Pathway activity inference in bulk RNA-seq","text":"infer pathway enrichment scores run Multivariate Linear Model (mlm) method. sample dataset (mat), fits linear model predicts observed gene expression based pathways’ Pathway-Gene interactions weights. fitted, obtained t-values slopes scores. positive, interpret pathway active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Run mlm sample_acts <- run_mlm(mat=counts, net=net, .source='source', .target='target',                   .mor='weight', minsize = 5) sample_acts #> # A tibble: 84 × 5 #>    statistic source   condition       score  p_value #>    <chr>     <chr>    <chr>           <dbl>    <dbl> #>  1 mlm       Androgen PANC1.WT.Rep1 -0.692  0.489    #>  2 mlm       EGFR     PANC1.WT.Rep1 -0.0414 0.967    #>  3 mlm       Estrogen PANC1.WT.Rep1 -0.361  0.718    #>  4 mlm       Hypoxia  PANC1.WT.Rep1 -2.06   0.0393   #>  5 mlm       JAK-STAT PANC1.WT.Rep1 -0.166  0.868    #>  6 mlm       MAPK     PANC1.WT.Rep1 -0.509  0.611    #>  7 mlm       NFkB     PANC1.WT.Rep1 -2.84   0.00447  #>  8 mlm       PI3K     PANC1.WT.Rep1  3.53   0.000423 #>  9 mlm       TGFb     PANC1.WT.Rep1 -1.43   0.152    #> 10 mlm       TNFa     PANC1.WT.Rep1  2.06   0.0395   #> # ℹ 74 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Pathway activity inference in bulk RNA-seq","text":"obtained results observe obtained activities per sample heat-map:  can also infer pathway activities t-values DEGs KO WT: Let’s show changes activity KO WT:  pathway p53 Trail deactivated KO compared WT, MAPKK JAK-STAT seem activated. can visualize responsive genes pathway along t-values interpret results. example, let’s see genes belong MAPK pathway:  pathway seems active since majority target genes positive weights positive t-values (1st quadrant), majority ones negative weights negative t-values (3d quadrant).","code":"# Transform to wide matrix sample_acts_mat <- sample_acts %>%   pivot_wider(id_cols = 'condition', names_from = 'source',               values_from = 'score') %>%   column_to_rownames('condition') %>%   as.matrix()  # Scale per feature sample_acts_mat <- scale(sample_acts_mat)  # Choose color palette palette_length = 100 my_color = colorRampPalette(c(\"Darkblue\", \"white\",\"red\"))(palette_length)  my_breaks <- c(seq(-3, 0, length.out=ceiling(palette_length/2) + 1),                seq(0.05, 3, length.out=floor(palette_length/2)))  # Plot pheatmap(sample_acts_mat, border_color = NA, color=my_color, breaks = my_breaks) # Run mlm contrast_acts <- run_mlm(mat=deg, net=net, .source='source', .target='target',                   .mor='weight', minsize = 5) contrast_acts #> # A tibble: 14 × 5 #>    statistic source   condition  score  p_value #>    <chr>     <chr>    <chr>      <dbl>    <dbl> #>  1 mlm       Androgen t         -0.219 8.27e- 1 #>  2 mlm       EGFR     t         -0.439 6.61e- 1 #>  3 mlm       Estrogen t          3.95  7.70e- 5 #>  4 mlm       Hypoxia  t          0.171 8.64e- 1 #>  5 mlm       JAK-STAT t          5.91  3.47e- 9 #>  6 mlm       MAPK     t         13.0   4.32e-38 #>  7 mlm       NFkB     t          1.36  1.75e- 1 #>  8 mlm       PI3K     t          5.65  1.65e- 8 #>  9 mlm       TGFb     t         -0.656 5.12e- 1 #> 10 mlm       TNFa     t          1.93  5.36e- 2 #> 11 mlm       Trail    t         -2.03  4.26e- 2 #> 12 mlm       VEGF     t          2.82  4.80e- 3 #> 13 mlm       WNT      t         -1.49  1.35e- 1 #> 14 mlm       p53      t         -4.80  1.60e- 6 # Plot ggplot(contrast_acts, aes(x = reorder(source, score), y = score)) +      geom_bar(aes(fill = score), stat = \"identity\") +     scale_fill_gradient2(low = \"darkblue\", high = \"indianred\",          mid = \"whitesmoke\", midpoint = 0) +      theme_minimal() +     theme(axis.title = element_text(face = \"bold\", size = 12),         axis.text.x =              element_text(angle = 45, hjust = 1, size =10, face= \"bold\"),         axis.text.y = element_text(size =10, face= \"bold\"),         panel.grid.major = element_blank(),          panel.grid.minor = element_blank()) +     xlab(\"Pathways\") pathway <- 'MAPK'  df <- net %>%   filter(source == pathway) %>%   arrange(target) %>%   mutate(ID = target, color = \"3\") %>%   column_to_rownames('target') inter <- sort(intersect(rownames(deg),rownames(df))) df <- df[inter, ] df['t_value'] <- deg[inter, ] df <- df %>%   mutate(color = if_else(weight > 0 & t_value > 0, '1', color)) %>%   mutate(color = if_else(weight > 0 & t_value < 0, '2', color)) %>%   mutate(color = if_else(weight < 0 & t_value > 0, '2', color)) %>%   mutate(color = if_else(weight < 0 & t_value < 0, '1', color))  ggplot(df, aes(x = weight, y = t_value, color = color)) + geom_point() +   scale_colour_manual(values = c(\"red\",\"royalblue3\",\"grey\")) +   geom_label_repel(aes(label = ID)) +    theme_minimal() +   theme(legend.position = \"none\") +   geom_vline(xintercept = 0, linetype = 'dotted') +   geom_hline(yintercept = 0, linetype = 'dotted') +   ggtitle(pathway) #> Warning: ggrepel: 447 unlabeled data points (too many overlaps). Consider #> increasing max.overlaps"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Pathway activity inference in bulk RNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R Under development (unstable) (2024-04-03 r86327) #>  os       Ubuntu 22.04.4 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-04-11 #>  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package      * version date (UTC) lib source #>  backports      1.4.1   2021-12-13 [1] CRAN (R 4.5.0) #>  BiocManager    1.30.22 2023-08-08 [1] CRAN (R 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──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Pathway activity inference from scRNA-seq","text":"First, need load relevant packages, Seurat handle scRNA-seq data decoupleR use statistical methods.","code":"## We load the required packages library(Seurat) library(decoupleR)  # Only needed for data handling and plotting library(dplyr) library(tibble) library(tidyr) library(patchwork) library(ggplot2) library(pheatmap)"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Pathway activity inference from scRNA-seq","text":"used -sampled version data used Seurat vignette. can open data like : can observe different cell types:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"sc_data.rds\")) DimPlot(data, reduction = \"umap\", label = TRUE, pt.size = 0.5) + NoLegend()"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"progeny-model","dir":"Articles","previous_headings":"Loading the data-set","what":"PROGENy model","title":"Pathway activity inference from scRNA-seq","text":"PROGENy comprehensive resource containing curated collection pathways target genes, weights interaction. example use human weights (organisms available) use top 500 responsive genes ranked p-value. brief description pathway: Androgen: involved growth development male reproductive organs. EGFR: regulates growth, survival, migration, apoptosis, proliferation, differentiation mammalian cells Estrogen: promotes growth development female reproductive organs. Hypoxia: promotes angiogenesis metabolic reprogramming O2 levels low. JAK-STAT: involved immunity, cell division, cell death, tumor formation. MAPK: integrates external signals promotes cell growth proliferation. NFkB: regulates immune response, cytokine production cell survival. p53: regulates cell cycle, apoptosis, DNA repair tumor suppression. PI3K: promotes growth proliferation. TGFb: involved development, homeostasis, repair tissues. TNFa: mediates haematopoiesis, immune surveillance, tumour regression protection infection. Trail: induces apoptosis. VEGF: mediates angiogenesis, vascular permeability, cell migration. WNT: regulates organ morphogenesis development tissue repair. access can use decoupleR:","code":"net <- get_progeny(organism = 'human', top = 500) net #> # A tibble: 7,000 × 4 #>    source   target  weight  p_value #>    <chr>    <chr>    <dbl>    <dbl> #>  1 Androgen TMPRSS2  11.5  2.38e-47 #>  2 Androgen NKX3-1   10.6  2.21e-44 #>  3 Androgen MBOAT2   10.5  4.63e-44 #>  4 Androgen KLK2     10.2  1.94e-40 #>  5 Androgen SARG     11.4  2.79e-40 #>  6 Androgen SLC38A4   7.36 1.25e-39 #>  7 Androgen MTMR9     6.13 2.53e-38 #>  8 Androgen ZBTB16   10.6  1.57e-36 #>  9 Androgen KCNN2     9.47 7.71e-36 #> 10 Androgen OPRK1    -5.63 1.11e-35 #> # ℹ 6,990 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"activity-inference-with-multivariate-linear-model-mlm","dir":"Articles","previous_headings":"","what":"Activity inference with Multivariate Linear Model (MLM)","title":"Pathway activity inference from scRNA-seq","text":"infer pathway enrichment scores run Multivariate Linear Model (mlm) method. sample dataset (mat), fits linear model predicts observed gene expression based pathways’ Pathway-Gene interactions weights. fitted, obtained t-values slopes scores. positive, interpret pathway active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Extract the normalized log-transformed counts mat <- as.matrix(data@assays$RNA@data)  # Run mlm acts <- run_mlm(mat=mat, net=net, .source='source', .target='target',                 .mor='weight', minsize = 5) acts #> # A tibble: 2,240 × 5 #>    statistic source   condition         score  p_value #>    <chr>     <chr>    <chr>             <dbl>    <dbl> #>  1 mlm       Androgen AAACATACAACCAC-1  0.559 0.576    #>  2 mlm       EGFR     AAACATACAACCAC-1  3.63  0.000290 #>  3 mlm       Estrogen AAACATACAACCAC-1 -0.886 0.375    #>  4 mlm       Hypoxia  AAACATACAACCAC-1  1.22  0.224    #>  5 mlm       JAK-STAT AAACATACAACCAC-1 -1.02  0.308    #>  6 mlm       MAPK     AAACATACAACCAC-1 -2.74  0.00619  #>  7 mlm       NFkB     AAACATACAACCAC-1 -0.230 0.818    #>  8 mlm       PI3K     AAACATACAACCAC-1 -1.09  0.276    #>  9 mlm       TGFb     AAACATACAACCAC-1  0.248 0.804    #> 10 mlm       TNFa     AAACATACAACCAC-1  2.22  0.0264   #> # ℹ 2,230 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Pathway activity inference from scRNA-seq","text":"obtained results, select ulm activities store object new assay called pathwaysmlm: new assay can used plot activities. visualize Trail pathway, associated apoptosis, seems B NK cells active.","code":"# Extract mlm and store it in pathwaysmlm in data data[['pathwaysmlm']] <- acts %>%   pivot_wider(id_cols = 'source', names_from = 'condition',               values_from = 'score') %>%   column_to_rownames('source') %>%   Seurat::CreateAssayObject(.)  # Change assay DefaultAssay(object = data) <- \"pathwaysmlm\"  # Scale the data data <- ScaleData(data) data@assays$pathwaysmlm@data <- data@assays$pathwaysmlm@scale.data p1 <- DimPlot(data, reduction = \"umap\", label = TRUE, pt.size = 0.5) +    NoLegend() + ggtitle('Cell types') p2 <- (FeaturePlot(data, features = c(\"Trail\")) &    scale_colour_gradient2(low = 'blue', mid = 'white', high = 'red')) +   ggtitle('Trail activity') p1 | p2"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"exploration","dir":"Articles","previous_headings":"","what":"Exploration","title":"Pathway activity inference from scRNA-seq","text":"can also see mean activity per group across pathways:  specific example, can observe Trail active B NK cells.","code":"# Extract activities from object as a long dataframe df <- t(as.matrix(data@assays$pathwaysmlm@data)) %>%   as.data.frame() %>%   mutate(cluster = Idents(data)) %>%   pivot_longer(cols = -cluster, names_to = \"source\", values_to = \"score\") %>%   group_by(cluster, source) %>%   summarise(mean = mean(score))  # Transform to wide matrix top_acts_mat <- df %>%   pivot_wider(id_cols = 'cluster', names_from = 'source',               values_from = 'mean') %>%   column_to_rownames('cluster') %>%   as.matrix()  # Choose color palette palette_length = 100 my_color = colorRampPalette(c(\"Darkblue\", \"white\",\"red\"))(palette_length)  my_breaks <- c(seq(-2, 0, length.out=ceiling(palette_length/2) + 1),                seq(0.05, 2, length.out=floor(palette_length/2)))  # Plot pheatmap(top_acts_mat, border_color = NA, color=my_color, breaks = my_breaks)"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Pathway activity inference from scRNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R Under development (unstable) (2024-04-03 r86327) #>  os       Ubuntu 22.04.4 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-04-11 #>  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package          * version  date (UTC) lib source #>  abind              1.4-5    2016-07-21 [1] CRAN (R 4.5.0) #>  backports          1.4.1    2021-12-13 [1] CRAN (R 4.5.0) #>  BiocManager        1.30.22  2023-08-08 [1] CRAN (R 4.5.0) #>  BiocParallel       1.37.1   2024-03-04 [1] Bioconduc~ #>  BiocStyle        * 2.31.0   2023-10-24 [1] Bioconductor #>  bit                4.0.5    2022-11-15 [1] CRAN (R 4.5.0) #>  bit64              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        * 1.3.1    2024-01-24 [1] CRAN (R 4.5.0) #>  tidyselect         1.2.1    2024-03-11 [1] CRAN (R 4.5.0) #>  timechange         0.3.0    2024-01-18 [1] CRAN (R 4.5.0) #>  tzdb               0.4.0    2023-05-12 [1] CRAN (R 4.5.0) #>  utf8               1.2.4    2023-10-22 [1] CRAN (R 4.5.0) #>  uwot               0.1.16   2023-06-29 [1] CRAN (R 4.5.0) #>  vctrs              0.6.5    2023-12-01 [1] CRAN (R 4.5.0) #>  viridisLite        0.4.2    2023-05-02 [1] CRAN (R 4.5.0) #>  vroom              1.6.5    2023-12-05 [1] CRAN (R 4.5.0) #>  withr              3.0.0    2024-01-16 [1] CRAN (R 4.5.0) #>  xfun               0.43     2024-03-25 [1] CRAN (R 4.5.0) #>  xml2               1.3.6    2023-12-04 [1] CRAN (R 4.5.0) #>  xtable             1.8-4    2019-04-21 [1] CRAN (R 4.5.0) #>  yaml               2.3.8    2023-12-11 [1] CRAN (R 4.5.0) #>  zoo                1.8-12   2023-04-13 [1] CRAN (R 4.5.0) #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Transcription factor activity inference in bulk RNA-seq","text":"First, need load relevant packages:","code":"## We load the required packages library(decoupleR) library(dplyr) library(tibble) library(tidyr) library(ggplot2) library(pheatmap) library(ggrepel)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Transcription factor activity inference in bulk RNA-seq","text":"used already processed bulk RNA-seq data-set. provide normalized log-transformed counts, experimental design meta-data Differential Expressed Genes (DEGs) obtained using limma. example use limma used DeSeq2, edgeR statistical framework. decoupleR requires gene level statistic perform enrichment analysis agnostic generated. However, recommend use statistics include direction change significance, example t-value obtained limma(t) DeSeq2(stat). edgeR return statistic can create weighting obtained logFC pvalue formula: -log10(pvalue) * logFC. can open data like : data can extract mentioned information. see normalized log-transformed counts: design meta-data: results limma, interested extracting obtained t-value p-value contrast:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"bk_data.rds\")) # Remove NAs and set row names counts <- data$counts %>%   dplyr::mutate_if(~ any(is.na(.x)), ~ if_else(is.na(.x),0,.x)) %>%    column_to_rownames(var = \"gene\") %>%    as.matrix() head(counts) #>          PANC1.WT.Rep1 PANC1.WT.Rep2 PANC1.WT.Rep3 PANC1.FOXA2KO.Rep1 #> NOC2L        10.052588     11.949123     12.057774          12.312291 #> PLEKHN1       7.535115      8.125993      8.714880           8.048196 #> PERM1         6.281242      6.424582      6.589668           6.293285 #> ISG15        10.938252     11.469081     11.425415          11.549986 #> AGRN          6.956335      7.196108      7.522550           7.061549 #> C1orf159      9.546224      9.788721      9.794589           9.850830 #>          PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO.Rep3 #> NOC2L             12.139918          11.494205 #> PLEKHN1            8.290154           8.621239 #> PERM1              6.486136           6.775344 #> ISG15             11.371464          11.178157 #> AGRN               7.485534           7.071555 #> C1orf159           9.988069           9.965357 design <- data$design design #> # A tibble: 6 × 2 #>   sample             condition     #>   <chr>              <chr>         #> 1 PANC1.WT.Rep1      PANC1.WT      #> 2 PANC1.WT.Rep2      PANC1.WT      #> 3 PANC1.WT.Rep3      PANC1.WT      #> 4 PANC1.FOXA2KO.Rep1 PANC1.FOXA2KO #> 5 PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO #> 6 PANC1.FOXA2KO.Rep3 PANC1.FOXA2KO # Extract t-values per gene deg <- data$limma_ttop %>%     select(ID, logFC, t, P.Value) %>%      filter(!is.na(t)) %>%      column_to_rownames(var = \"ID\") %>%     as.matrix() head(deg) #>             logFC          t      P.Value #> RHBDL2  -1.823940 -12.810588 3.030276e-06 #> PLEKHH2 -1.568830 -10.794453 9.932046e-06 #> HEG1    -1.725806  -9.788112 1.939734e-05 #> CLU     -1.786200  -9.761618 1.975813e-05 #> FHL1     2.087082   8.950191 3.552199e-05 #> RBP4    -1.728960  -8.529074 4.904579e-05"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"collectri-network","dir":"Articles","previous_headings":"","what":"CollecTRI network","title":"Transcription factor activity inference in bulk RNA-seq","text":"CollecTRI comprehensive resource containing curated collection TFs transcriptional targets compiled 12 different resources. collection provides increased coverage transcription factors superior performance identifying perturbed TFs compared previous DoRothEA network literature based GRNs. Similar DoRothEA, interactions weighted mode regulation (activation inhibition). example use human version (mouse rat also available). can use decoupleR retrieve OmniPath. argument split_complexes keeps complexes splits subunits, default recommend keep complexes together.","code":"net <- get_collectri(organism='human', split_complexes=FALSE) net #> # A tibble: 43,178 × 3 #>    source target   mor #>    <chr>  <chr>  <dbl> #>  1 MYC    TERT       1 #>  2 SPI1   BGLAP      1 #>  3 SMAD3  JUN        1 #>  4 SMAD4  JUN        1 #>  5 STAT5A IL2        1 #>  6 STAT5B IL2        1 #>  7 RELA   FAS        1 #>  8 WT1    NR0B1      1 #>  9 NR0B2  CASP1      1 #> 10 SP1    ALDOA      1 #> # ℹ 43,168 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"activity-inference-with-univariate-linear-model-ulm","dir":"Articles","previous_headings":"","what":"Activity inference with Univariate Linear Model (ULM)","title":"Transcription factor activity inference in bulk RNA-seq","text":"infer TF enrichment scores run Univariate Linear Model (ulm) method. sample dataset (mat) TF network (net), fits linear model predicts observed gene expression based solely TF’s TF-Gene interaction weights. fitted, obtained t-value slope score. positive, interpret TF active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Run ulm sample_acts <- run_ulm(mat=counts, net=net, .source='source', .target='target',                   .mor='mor', minsize = 5) sample_acts #> # A tibble: 3,480 × 5 #>    statistic source condition           score p_value #>    <chr>     <chr>  <chr>               <dbl>   <dbl> #>  1 ulm       ABL1   PANC1.FOXA2KO.Rep1 -0.428  0.669  #>  2 ulm       ABL1   PANC1.FOXA2KO.Rep2 -0.104  0.917  #>  3 ulm       ABL1   PANC1.FOXA2KO.Rep3  0.335  0.738  #>  4 ulm       ABL1   PANC1.WT.Rep1       0.142  0.887  #>  5 ulm       ABL1   PANC1.WT.Rep2      -0.344  0.731  #>  6 ulm       ABL1   PANC1.WT.Rep3      -0.523  0.601  #>  7 ulm       AHR    PANC1.FOXA2KO.Rep1  1.58   0.113  #>  8 ulm       AHR    PANC1.FOXA2KO.Rep2  1.70   0.0885 #>  9 ulm       AHR    PANC1.FOXA2KO.Rep3  1.85   0.0640 #> 10 ulm       AHR    PANC1.WT.Rep1       1.38   0.169  #> # ℹ 3,470 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Transcription factor activity inference in bulk RNA-seq","text":"obtained results observe variable activities across samples heat-map:  can also infer TF activities t-values DEGs KO WT: Let’s show changes activity KO WT:  TFs GLI3 SPDEF deactivated KO compared WT, MUC NFKB1 seem activated. can visualize differential target genes TF along p-values interpret results. example, let’s see genes belong SP1:  blue means sign multiplying mor t-value negative, meaning genes “deactivating” TF, red means sign positive, meaning genes “activating” TF.","code":"n_tfs <- 25  # Transform to wide matrix sample_acts_mat <- sample_acts %>%   pivot_wider(id_cols = 'condition', names_from = 'source',               values_from = 'score') %>%   column_to_rownames('condition') %>%   as.matrix()  # Get top tfs with more variable means across clusters tfs <- sample_acts %>%   group_by(source) %>%   summarise(std = sd(score)) %>%   arrange(-abs(std)) %>%   head(n_tfs) %>%   pull(source) sample_acts_mat <- sample_acts_mat[,tfs]  # Scale per sample sample_acts_mat <- scale(sample_acts_mat)  # Choose color palette palette_length = 100 my_color = colorRampPalette(c(\"Darkblue\", \"white\",\"red\"))(palette_length)  my_breaks <- c(seq(-3, 0, length.out=ceiling(palette_length/2) + 1),                seq(0.05, 3, length.out=floor(palette_length/2)))  # Plot pheatmap(sample_acts_mat, border_color = NA, color=my_color, breaks = my_breaks) # Run ulm contrast_acts <- run_ulm(mat=deg[, 't', drop=FALSE], net=net, .source='source', .target='target',                   .mor='mor', minsize = 5) contrast_acts #> # A tibble: 580 × 5 #>    statistic source condition   score p_value #>    <chr>     <chr>  <chr>       <dbl>   <dbl> #>  1 ulm       ABL1   t          1.08    0.280  #>  2 ulm       AHR    t          1.19    0.234  #>  3 ulm       AIRE   t         -0.155   0.877  #>  4 ulm       AP1    t          2.42    0.0154 #>  5 ulm       APEX1  t          0.877   0.380  #>  6 ulm       AR     t         -0.264   0.792  #>  7 ulm       ARID1A t         -0.236   0.813  #>  8 ulm       ARID3A t          1.85    0.0639 #>  9 ulm       ARID3B t          1.24    0.215  #> 10 ulm       ARID4A t         -0.0674  0.946  #> # ℹ 570 more rows # Filter top TFs in both signs f_contrast_acts <- contrast_acts %>%   mutate(rnk = NA) msk <- f_contrast_acts$score > 0 f_contrast_acts[msk, 'rnk'] <- rank(-f_contrast_acts[msk, 'score']) f_contrast_acts[!msk, 'rnk'] <- rank(-abs(f_contrast_acts[!msk, 'score'])) tfs <- f_contrast_acts %>%   arrange(rnk) %>%   head(n_tfs) %>%   pull(source) f_contrast_acts <- f_contrast_acts %>%   filter(source %in% tfs)  # Plot ggplot(f_contrast_acts, aes(x = reorder(source, score), y = score)) +      geom_bar(aes(fill = score), stat = \"identity\") +     scale_fill_gradient2(low = \"darkblue\", high = \"indianred\",          mid = \"whitesmoke\", midpoint = 0) +      theme_minimal() +     theme(axis.title = element_text(face = \"bold\", size = 12),         axis.text.x =              element_text(angle = 45, hjust = 1, size =10, face= \"bold\"),         axis.text.y = element_text(size =10, face= \"bold\"),         panel.grid.major = element_blank(),          panel.grid.minor = element_blank()) +     xlab(\"TFs\") tf <- 'SP1'  df <- net %>%   filter(source == tf) %>%   arrange(target) %>%   mutate(ID = target, color = \"3\") %>%   column_to_rownames('target')  inter <- sort(intersect(rownames(deg),rownames(df))) df <- df[inter, ] df[,c('logfc', 't_value', 'p_value')] <- deg[inter, ] df <- df %>%   mutate(color = if_else(mor > 0 & t_value > 0, '1', color)) %>%   mutate(color = if_else(mor > 0 & t_value < 0, '2', color)) %>%   mutate(color = if_else(mor < 0 & t_value > 0, '2', color)) %>%   mutate(color = if_else(mor < 0 & t_value < 0, '1', color))  ggplot(df, aes(x = logfc, y = -log10(p_value), color = color, size=abs(mor))) +   geom_point() +   scale_colour_manual(values = c(\"red\",\"royalblue3\",\"grey\")) +   geom_label_repel(aes(label = ID, size=1)) +    theme_minimal() +   theme(legend.position = \"none\") +   geom_vline(xintercept = 0, linetype = 'dotted') +   geom_hline(yintercept = 0, linetype = 'dotted') +   ggtitle(tf)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Transcription factor activity inference in bulk RNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R Under development (unstable) (2024-04-03 r86327) #>  os       Ubuntu 22.04.4 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-04-11 #>  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package      * version date (UTC) lib source #>  backports      1.4.1   2021-12-13 [1] CRAN (R 4.5.0) #>  BiocManager    1.30.22 2023-08-08 [1] CRAN (R 4.5.0) #>  BiocParallel   1.37.1  2024-03-04 [1] Bioconduc~ #>  BiocStyle    * 2.31.0  2023-10-24 [1] Bioconductor #>  bit            4.0.5   2022-11-15 [1] CRAN (R 4.5.0) #>  bit64          4.0.5   2020-08-30 [1] CRAN (R 4.5.0) #>  bookdown       0.38    2024-03-04 [1] CRAN (R 4.5.0) #>  bslib          0.7.0   2024-03-29 [1] CRAN (R 4.5.0) #>  cachem         1.0.8   2023-05-01 [1] CRAN (R 4.5.0) #>  cellranger     1.1.0   2016-07-27 [1] CRAN (R 4.5.0) #>  checkmate      2.3.1   2023-12-04 [1] CRAN (R 4.5.0) #>  cli            3.6.2   2023-12-11 [1] CRAN (R 4.5.0) #>  codetools      0.2-20  2024-03-31 [2] CRAN (R 4.5.0) #>  colorspace     2.1-0   2023-01-23 [1] CRAN (R 4.5.0) #>  crayon         1.5.2   2022-09-29 [1] CRAN (R 4.5.0) #>  curl           5.2.1   2024-03-01 [1] CRAN (R 4.5.0) #>  decoupleR    * 2.9.7   2024-04-11 [1] Bioconductor #>  desc           1.4.3   2023-12-10 [1] CRAN (R 4.5.0) #>  digest         0.6.35  2024-03-11 [1] CRAN (R 4.5.0) #>  dplyr        * 1.1.4   2023-11-17 [1] CRAN (R 4.5.0) #>  evaluate       0.23    2023-11-01 [1] CRAN (R 4.5.0) #>  fansi          1.0.6   2023-12-08 [1] CRAN (R 4.5.0) #>  farver         2.1.1   2022-07-06 [1] CRAN (R 4.5.0) #>  fastmap        1.1.1   2023-02-24 [1] CRAN (R 4.5.0) #>  fs             1.6.3   2023-07-20 [1] CRAN (R 4.5.0) #>  generics       0.1.3   2022-07-05 [1] CRAN (R 4.5.0) #>  ggplot2      * 3.5.0   2024-02-23 [1] CRAN (R 4.5.0) #>  ggrepel      * 0.9.5   2024-01-10 [1] CRAN (R 4.5.0) #>  glue           1.7.0   2024-01-09 [1] CRAN (R 4.5.0) #>  gtable         0.3.4   2023-08-21 [1] CRAN (R 4.5.0) #>  highr          0.10    2022-12-22 [1] CRAN (R 4.5.0) #>  hms            1.1.3   2023-03-21 [1] CRAN (R 4.5.0) #>  htmltools      0.5.8.1 2024-04-04 [1] CRAN (R 4.5.0) #>  htmlwidgets    1.6.4   2023-12-06 [1] CRAN (R 4.5.0) #>  httr           1.4.7   2023-08-15 [1] CRAN (R 4.5.0) #>  igraph         2.0.3   2024-03-13 [1] CRAN (R 4.5.0) #>  jquerylib      0.1.4   2021-04-26 [1] CRAN (R 4.5.0) #>  jsonlite       1.8.8   2023-12-04 [1] CRAN (R 4.5.0) #>  knitr          1.46    2024-04-06 [1] CRAN (R 4.5.0) #>  labeling       0.4.3   2023-08-29 [1] CRAN (R 4.5.0) #>  later          1.3.2   2023-12-06 [1] CRAN (R 4.5.0) #>  lattice        0.22-6  2024-03-20 [2] CRAN (R 4.5.0) #>  lifecycle      1.0.4   2023-11-07 [1] CRAN (R 4.5.0) #>  logger         0.3.0   2024-03-05 [1] CRAN (R 4.5.0) #>  lubridate      1.9.3   2023-09-27 [1] CRAN (R 4.5.0) #>  magrittr       2.0.3   2022-03-30 [1] CRAN (R 4.5.0) #>  Matrix         1.7-0   2024-03-22 [2] CRAN (R 4.5.0) #>  memoise        2.0.1   2021-11-26 [1] CRAN (R 4.5.0) #>  munsell        0.5.1   2024-04-01 [1] CRAN (R 4.5.0) #>  OmnipathR      3.11.10 2024-03-24 [1] Bioconduc~ #>  parallelly     1.37.1  2024-02-29 [1] CRAN (R 4.5.0) #>  pheatmap     * 1.0.12  2019-01-04 [1] CRAN (R 4.5.0) #>  pillar         1.9.0   2023-03-22 [1] CRAN (R 4.5.0) #>  pkgconfig      2.0.3   2019-09-22 [1] CRAN (R 4.5.0) #>  pkgdown        2.0.8   2024-04-10 [1] CRAN (R 4.5.0) #>  prettyunits    1.2.0   2023-09-24 [1] CRAN (R 4.5.0) #>  progress       1.2.3   2023-12-06 [1] CRAN (R 4.5.0) #>  purrr          1.0.2   2023-08-10 [1] CRAN (R 4.5.0) #>  R6             2.5.1   2021-08-19 [1] CRAN (R 4.5.0) #>  ragg           1.3.0   2024-03-13 [1] CRAN (R 4.5.0) #>  rappdirs       0.3.3   2021-01-31 [1] CRAN (R 4.5.0) #>  RColorBrewer   1.1-3   2022-04-03 [1] CRAN (R 4.5.0) #>  Rcpp           1.0.12  2024-01-09 [1] CRAN (R 4.5.0) #>  readr          2.1.5   2024-01-10 [1] CRAN (R 4.5.0) #>  readxl         1.4.3   2023-07-06 [1] CRAN (R 4.5.0) #>  rlang          1.1.3   2024-01-10 [1] CRAN (R 4.5.0) #>  rmarkdown      2.26    2024-03-05 [1] CRAN (R 4.5.0) #>  rvest          1.0.4   2024-02-12 [1] CRAN (R 4.5.0) #>  sass           0.4.9   2024-03-15 [1] CRAN (R 4.5.0) #>  scales         1.3.0   2023-11-28 [1] CRAN (R 4.5.0) #>  selectr        0.4-2   2019-11-20 [1] CRAN (R 4.5.0) #>  sessioninfo    1.2.2   2021-12-06 [1] CRAN (R 4.5.0) #>  stringi        1.8.3   2023-12-11 [1] CRAN (R 4.5.0) #>  stringr        1.5.1   2023-11-14 [1] CRAN (R 4.5.0) #>  systemfonts    1.0.6   2024-03-07 [1] CRAN (R 4.5.0) #>  textshaping    0.3.7   2023-10-09 [1] CRAN (R 4.5.0) #>  tibble       * 3.2.1   2023-03-20 [1] CRAN (R 4.5.0) #>  tidyr        * 1.3.1   2024-01-24 [1] CRAN (R 4.5.0) #>  tidyselect     1.2.1   2024-03-11 [1] CRAN (R 4.5.0) #>  timechange     0.3.0   2024-01-18 [1] CRAN (R 4.5.0) #>  tzdb           0.4.0   2023-05-12 [1] CRAN (R 4.5.0) #>  utf8           1.2.4   2023-10-22 [1] CRAN (R 4.5.0) #>  vctrs          0.6.5   2023-12-01 [1] CRAN (R 4.5.0) #>  vroom          1.6.5   2023-12-05 [1] CRAN (R 4.5.0) #>  withr          3.0.0   2024-01-16 [1] CRAN (R 4.5.0) #>  xfun           0.43    2024-03-25 [1] CRAN (R 4.5.0) #>  xml2           1.3.6   2023-12-04 [1] CRAN (R 4.5.0) #>  yaml           2.3.8   2023-12-11 [1] CRAN (R 4.5.0) #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Transcription factor activity inference from scRNA-seq","text":"First, need load relevant packages, Seurat handle scRNA-seq data decoupleR use statistical methods.","code":"## We load the required packages library(Seurat) library(decoupleR)  # Only needed for data handling and plotting library(dplyr) library(tibble) library(tidyr) library(patchwork) library(ggplot2) library(pheatmap)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Transcription factor activity inference from scRNA-seq","text":"used -sampled version data used Seurat vignette. can open data like : can observe different cell types:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"sc_data.rds\")) DimPlot(data, reduction = \"umap\", label = TRUE, pt.size = 0.5) + NoLegend()"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"collectri-network","dir":"Articles","previous_headings":"","what":"CollecTRI network","title":"Transcription factor activity inference from scRNA-seq","text":"CollecTRI comprehensive resource containing curated collection TFs transcriptional targets compiled 12 different resources. collection provides increased coverage transcription factors superior performance identifying perturbed TFs compared previous DoRothEA network literature based GRNs. Similar DoRothEA, interactions weighted mode regulation (activation inhibition). example use human version (mouse rat also available). can use decoupleR retrieve OmniPath. argument split_complexes keeps complexes splits subunits, default recommend keep complexes together.","code":"net <- get_collectri(organism='human', split_complexes=FALSE) net #> # A tibble: 43,178 × 3 #>    source target   mor #>    <chr>  <chr>  <dbl> #>  1 MYC    TERT       1 #>  2 SPI1   BGLAP      1 #>  3 SMAD3  JUN        1 #>  4 SMAD4  JUN        1 #>  5 STAT5A IL2        1 #>  6 STAT5B IL2        1 #>  7 RELA   FAS        1 #>  8 WT1    NR0B1      1 #>  9 NR0B2  CASP1      1 #> 10 SP1    ALDOA      1 #> # ℹ 43,168 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"activity-inference-with-univariate-linear-model-ulm","dir":"Articles","previous_headings":"","what":"Activity inference with Univariate Linear Model (ULM)","title":"Transcription factor activity inference from scRNA-seq","text":"infer TF enrichment scores run Univariate Linear Model (ulm) method. sample dataset (mat) TF network (net), fits linear model predicts observed gene expression based solely TF’s TF-Gene interaction weights. fitted, obtained t-value slope score. positive, interpret TF active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Extract the normalized log-transformed counts mat <- as.matrix(data@assays$RNA@data)  # Run ulm acts <- run_ulm(mat=mat, net=net, .source='source', .target='target',                 .mor='mor', minsize = 5) acts #> # A tibble: 80,640 × 5 #>    statistic source condition         score p_value #>    <chr>     <chr>  <chr>             <dbl>   <dbl> #>  1 ulm       ABL1   AAACATACAACCAC-1  2.64  0.00820 #>  2 ulm       ABL1   AAACGCTGTTTCTG-1  0.893 0.372   #>  3 ulm       ABL1   AACCTTTGGACGGA-1  2.79  0.00525 #>  4 ulm       ABL1   AACGCCCTCGTACA-1  1.80  0.0721  #>  5 ulm       ABL1   AACGTCGAGTATCG-1  1.63  0.104   #>  6 ulm       ABL1   AACTCACTCAAGCT-1  1.71  0.0871  #>  7 ulm       ABL1   AAGATGGAAAACAG-1  1.12  0.264   #>  8 ulm       ABL1   AAGATTACCGCCTT-1  2.43  0.0151  #>  9 ulm       ABL1   AAGCCATGAACTGC-1  1.62  0.105   #> 10 ulm       ABL1   AAGGTCTGCAGATC-1 -0.292 0.771   #> # ℹ 80,630 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Transcription factor activity inference from scRNA-seq","text":"obtained results, store object new assay called tfsulm: new assay can used plot activities. observe activity inferred PAX5 across cells, particulary active B cells. Interestingly, PAX5 known TF crucial B cell identity function. inference activities “foot-prints” target genes informative just looking molecular readouts given TF, example gene expression PAX5, informative :","code":"# Extract ulm and store it in tfsulm in pbmc data[['tfsulm']] <- acts %>%   pivot_wider(id_cols = 'source', names_from = 'condition',               values_from = 'score') %>%   column_to_rownames('source') %>%   Seurat::CreateAssayObject(.)  # Change assay DefaultAssay(object = data) <- \"tfsulm\"  # Scale the data data <- ScaleData(data) data@assays$tfsulm@data <- data@assays$tfsulm@scale.data p1 <- DimPlot(data, reduction = \"umap\", label = TRUE, pt.size = 0.5) +    NoLegend() + ggtitle('Cell types') p2 <- (FeaturePlot(data, features = c(\"PAX5\")) &    scale_colour_gradient2(low = 'blue', mid = 'white', high = 'red')) +   ggtitle('PAX5 activity') DefaultAssay(object = data) <- \"RNA\" p3 <- FeaturePlot(data, features = c(\"PAX5\")) + ggtitle('PAX5 expression') DefaultAssay(object = data) <- \"tfsulm\" p1 | p2 | p3"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"exploration","dir":"Articles","previous_headings":"","what":"Exploration","title":"Transcription factor activity inference from scRNA-seq","text":"can also see mean activity per group top 20 variable TFs:  can observe known marker TFs appearing, EBF1 B cells RFX5 myeloid lineage EOMES lymphoid.","code":"n_tfs <- 25 # Extract activities from object as a long dataframe df <- t(as.matrix(data@assays$tfsulm@data)) %>%   as.data.frame() %>%   mutate(cluster = Idents(data)) %>%   pivot_longer(cols = -cluster, names_to = \"source\", values_to = \"score\") %>%   group_by(cluster, source) %>%   summarise(mean = mean(score))  # Get top tfs with more variable means across clusters tfs <- df %>%   group_by(source) %>%   summarise(std = sd(mean)) %>%   arrange(-abs(std)) %>%   head(n_tfs) %>%   pull(source)  # Subset long data frame to top tfs and transform to wide matrix top_acts_mat <- df %>%   filter(source %in% tfs) %>%   pivot_wider(id_cols = 'cluster', names_from = 'source',               values_from = 'mean') %>%   column_to_rownames('cluster') %>%   as.matrix()  # Choose color palette palette_length = 100 my_color = colorRampPalette(c(\"Darkblue\", \"white\",\"red\"))(palette_length)  my_breaks <- c(seq(-3, 0, length.out=ceiling(palette_length/2) + 1),                seq(0.05, 3, length.out=floor(palette_length/2)))  # Plot pheatmap(top_acts_mat, border_color = NA, color=my_color, breaks = my_breaks)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Transcription factor activity inference from scRNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R Under development (unstable) (2024-04-03 r86327) #>  os       Ubuntu 22.04.4 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-04-11 #>  pandoc   3.1.1 @ /usr/local/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package          * version  date (UTC) lib source #>  abind              1.4-5    2016-07-21 [1] CRAN (R 4.5.0) #>  backports          1.4.1    2021-12-13 [1] CRAN (R 4.5.0) #>  BiocManager        1.30.22  2023-08-08 [1] CRAN (R 4.5.0) #>  BiocParallel       1.37.1   2024-03-04 [1] Bioconduc~ #>  BiocStyle        * 2.31.0   2023-10-24 [1] Bioconductor #>  bit                4.0.5    2022-11-15 [1] CRAN (R 4.5.0) #>  bit64              4.0.5    2020-08-30 [1] CRAN (R 4.5.0) #>  bookdown           0.38     2024-03-04 [1] CRAN (R 4.5.0) #>  bslib              0.7.0    2024-03-29 [1] CRAN (R 4.5.0) #>  cachem             1.0.8 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CRAN (R 4.5.0) #>  munsell            0.5.1    2024-04-01 [1] CRAN (R 4.5.0) #>  nlme               3.1-164  2023-11-27 [2] CRAN (R 4.5.0) #>  OmnipathR          3.11.10  2024-03-24 [1] Bioconduc~ #>  parallelly         1.37.1   2024-02-29 [1] CRAN (R 4.5.0) #>  patchwork        * 1.2.0    2024-01-08 [1] CRAN (R 4.5.0) #>  pbapply            1.7-2    2023-06-27 [1] CRAN (R 4.5.0) #>  pheatmap         * 1.0.12   2019-01-04 [1] CRAN (R 4.5.0) #>  pillar             1.9.0    2023-03-22 [1] CRAN (R 4.5.0) #>  pkgconfig          2.0.3    2019-09-22 [1] CRAN (R 4.5.0) #>  pkgdown            2.0.8    2024-04-10 [1] CRAN (R 4.5.0) #>  plotly             4.10.4   2024-01-13 [1] CRAN (R 4.5.0) #>  plyr               1.8.9    2023-10-02 [1] CRAN (R 4.5.0) #>  png                0.1-8    2022-11-29 [1] CRAN (R 4.5.0) #>  polyclip           1.10-6   2023-09-27 [1] CRAN (R 4.5.0) #>  prettyunits        1.2.0    2023-09-24 [1] CRAN (R 4.5.0) #>  progress           1.2.3    2023-12-06 [1] CRAN (R 4.5.0) #>  progressr          0.14.0   2023-08-10 [1] CRAN (R 4.5.0) #>  promises           1.3.0    2024-04-05 [1] CRAN (R 4.5.0) #>  purrr              1.0.2    2023-08-10 [1] CRAN (R 4.5.0) #>  R6                 2.5.1    2021-08-19 [1] CRAN (R 4.5.0) #>  ragg               1.3.0    2024-03-13 [1] CRAN (R 4.5.0) #>  RANN               2.6.1    2019-01-08 [1] CRAN (R 4.5.0) #>  rappdirs           0.3.3    2021-01-31 [1] CRAN (R 4.5.0) #>  RColorBrewer       1.1-3    2022-04-03 [1] CRAN (R 4.5.0) #>  Rcpp               1.0.12   2024-01-09 [1] CRAN (R 4.5.0) #>  RcppAnnoy          0.0.22   2024-01-23 [1] CRAN (R 4.5.0) #>  RcppHNSW           0.6.0    2024-02-04 [1] CRAN (R 4.5.0) #>  readr              2.1.5    2024-01-10 [1] CRAN (R 4.5.0) #>  readxl             1.4.3    2023-07-06 [1] CRAN (R 4.5.0) #>  reshape2           1.4.4    2020-04-09 [1] CRAN (R 4.5.0) #>  reticulate         1.35.0   2024-01-31 [1] CRAN (R 4.5.0) #>  rlang              1.1.3    2024-01-10 [1] CRAN (R 4.5.0) #>  rmarkdown          2.26     2024-03-05 [1] CRAN (R 4.5.0) #>  ROCR               1.0-11   2020-05-02 [1] CRAN (R 4.5.0) #>  RSpectra           0.16-1   2022-04-24 [1] CRAN (R 4.5.0) #>  Rtsne              0.17     2023-12-07 [1] CRAN (R 4.5.0) #>  rvest              1.0.4    2024-02-12 [1] CRAN (R 4.5.0) #>  sass               0.4.9    2024-03-15 [1] CRAN (R 4.5.0) #>  scales             1.3.0    2023-11-28 [1] CRAN (R 4.5.0) #>  scattermore        1.2      2023-06-12 [1] CRAN (R 4.5.0) #>  sctransform        0.4.1    2023-10-19 [1] CRAN (R 4.5.0) #>  selectr            0.4-2    2019-11-20 [1] CRAN (R 4.5.0) #>  sessioninfo        1.2.2    2021-12-06 [1] CRAN (R 4.5.0) #>  Seurat           * 5.0.3    2024-03-18 [1] CRAN (R 4.5.0) #>  SeuratObject     * 5.0.1    2023-11-17 [1] CRAN (R 4.5.0) #>  shiny              1.8.1.1  2024-04-02 [1] CRAN (R 4.5.0) #>  sp               * 2.1-3    2024-01-30 [1] CRAN (R 4.5.0) #>  spam               2.10-0   2023-10-23 [1] CRAN (R 4.5.0) #>  spatstat.data      3.0-4    2024-01-15 [1] CRAN (R 4.5.0) #>  spatstat.explore   3.2-7    2024-03-21 [1] CRAN (R 4.5.0) #>  spatstat.geom      3.2-9    2024-02-28 [1] CRAN (R 4.5.0) #>  spatstat.random    3.2-3    2024-02-29 [1] CRAN (R 4.5.0) #>  spatstat.sparse    3.0-3    2023-10-24 [1] CRAN (R 4.5.0) #>  spatstat.utils     3.0-4    2023-10-24 [1] CRAN (R 4.5.0) #>  stringi            1.8.3    2023-12-11 [1] CRAN (R 4.5.0) #>  stringr            1.5.1    2023-11-14 [1] CRAN (R 4.5.0) #>  survival           3.5-8    2024-02-14 [2] CRAN (R 4.5.0) #>  systemfonts        1.0.6    2024-03-07 [1] CRAN (R 4.5.0) #>  tensor             1.5      2012-05-05 [1] CRAN (R 4.5.0) #>  textshaping        0.3.7    2023-10-09 [1] CRAN (R 4.5.0) #>  tibble           * 3.2.1    2023-03-20 [1] CRAN (R 4.5.0) #>  tidyr            * 1.3.1    2024-01-24 [1] CRAN (R 4.5.0) #>  tidyselect         1.2.1    2024-03-11 [1] CRAN (R 4.5.0) #>  timechange         0.3.0    2024-01-18 [1] CRAN (R 4.5.0) #>  tzdb     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──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Pau Badia--Mompel. Author, maintainer. Jesús Vélez-Santiago. Author. Jana Braunger. Author. Celina Geiss. Author. Daniel Dimitrov. Author. Sophia Müller-Dott. Author. Petr Taus. Author. Aurélien Dugourd. Author. Christian H. Holland. Author. Ricardo O. Ramirez Flores. Author. Julio Saez-Rodriguez. Author.","code":""},{"path":"https://saezlab.github.io/decoupleR/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Badia--Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov    D., Müller-Dott S., Taus P., Dugourd ., Holland C.H., Ramirez Flores R.O.    Saez-Rodriguez J. 2022. decoupleR: Ensemble computational methods    infer biological activities omics data. Bioinformatics Advances.   https://doi.org/10.1093/bioadv/vbac016","code":"@Article{,   author = {Pau Badia-i-Mompel and Jesús Vélez Santiago and Jana Braunger and Celina Geiss and Daniel Dimitrov and Sophia Müller-Dott and Petr Taus and Aurelien Dugourd and Christian H. Holland and Ricardo O. Ramirez Flores and Julio Saez-Rodriguez},   title = {decoupleR: ensemble of computational methods to infer biological activities from omics data},   journal = {Bioinformatics Advances},   year = {2022},   doi = {https://doi.org/10.1093/bioadv/vbac016}, }"},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"many methods allow us extract biological activities omics data. decoupleR Bioconductor package containing different statistical methods extract biological signatures prior knowledge within unified framework. Additionally, incorporates methods take account sign weight network interactions. decoupleR can used omic, long features can linked biological process based prior knowledge. example, transcriptomics gene sets regulated transcription factor, phospho-proteomics phosphosites targeted kinase. R version, faster memory efficient Python implementation go .  information package used real data, please check following links: decoupleR’s general usage Pathway activity inference bulk RNA-seq Pathway activity inference scRNA-seq Transcription factor activity inference bulk RNA-seq Transcription factor activity inference scRNA-seq Example Kinase TF activity estimation decoupleR’s manuscript repository Python implementation","code":""},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"decoupleR R package distributed part Bioconductor project. install package, start R enter: Alternatively, find error, try install latest version GitHub:","code":"install.packages('BiocManager') BiocManager::install('saezlab/decoupleR') install.packages('remotes') remotes::install_github('saezlab/decoupleR')"},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"Footprint methods inside decoupleR can used academic commercial purposes, except viper holds non-commercial license. data redistributed OmniPath license, original resource carries . one can find license information resources OmniPath.","code":""},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"Badia--Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov D., Müller-Dott S., Taus P., Dugourd ., Holland C.H., Ramirez Flores R.O. Saez-Rodriguez J. 2022. decoupleR: ensemble computational methods infer biological activities omics data. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbac016","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":null,"dir":"Reference","previous_headings":"","what":"Check correlation (colinearity) — check_corr","title":"Check correlation (colinearity) — check_corr","text":"Checks correlation across regulators network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check correlation (colinearity) — check_corr","text":"","code":"check_corr(   network,   .source = \"source\",   .target = \"target\",   .mor = \"mor\",   .likelihood = NULL )"},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check correlation (colinearity) — check_corr","text":"network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check correlation (colinearity) — check_corr","text":"Correlation pairs tibble.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check correlation (colinearity) — check_corr","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") net <- readRDS(file.path(inputs_dir, \"net.rds\")) check_corr(net, .source='source') #> # A tibble: 3 × 3 #>   source source.2 correlation #>   <chr>  <chr>          <dbl> #> 1 T1     T3             0.364 #> 2 T2     T3            -0.487 #> 3 T1     T2            -0.688"},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":null,"dir":"Reference","previous_headings":"","what":"Rename columns and add defaults values if column not present — convert_f_defaults","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"convert_f_defaults() combine dplyr::rename() way working tibble::add_column() add columns default values case exist renaming data.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"","code":"convert_f_defaults(.data, ..., .def_col_val = c(), .use_dots = TRUE)"},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":".data data frame, data frame extension (e.g. tibble), lazy data frame (e.g. dbplyr dtplyr). See Methods, , details. ... rename(): <tidy-select> Use new_name = old_name rename selected variables. rename_with(): additional arguments passed onto .fn. .def_col_val Named vector columns default values none exist rename. .use_dots dot prefix added renamed variables? allow swapping columns.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"object type .data. output following properties: Rows affected. Column names changed. Column order function call.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"objective using .use_dots able swap columns , default, allowed dplyr::rename() function. behavior can replicated simply using dplyr::select(), however, select evaluation allows much flexibility unexpected results obtained. Despite , future implementation consider form execution allow renaming column multiple ones (.e. extend dataframe extension).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"","code":"df <- tibble::tibble(x = 1, y = 2, z = 3)  # Rename columns df <- tibble::tibble(x = 1, y = 2) convert_f_defaults(     .data = df,     new_x = x,     new_y = y,     new_z = NULL,     .def_col_val = c(new_z = 3) ) #> # A tibble: 1 × 3 #>   new_x new_y new_z #>   <dbl> <dbl> <dbl> #> 1     1     2     3"},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate multiple statistics with same input data — decouple","title":"Evaluate multiple statistics with same input data — decouple","text":"Calculate source activity per sample gene expression matrix coupling regulatory network variety statistics.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate multiple statistics with same input data — decouple","text":"","code":"decouple(   mat,   network,   .source = source,   .target = target,   statistics = NULL,   args = list(NULL),   consensus_score = TRUE,   consensus_stats = NULL,   include_time = FALSE,   show_toy_call = FALSE,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate multiple statistics with same input data — decouple","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. statistics Statistical methods run sequentially. none provided, top performer methods run (mlm, ulm wsum). args list argument-lists length statistics (length 1). default argument, list(NULL), recycled length statistics, call function arguments (apart mat, network, .source , .target). consensus_score Boolean whether run consensus score methods. consensus_stats List estimate names use calculation consensus score. used filter extra estimations methods, example wsum returns wsum, corr_wsum norm_wsum. none provided, also statstics provided, top performer methods used (mlm, ulm norm_wsum). Else, use available estimates running methods statistics argument. include_time time per statistic evaluated informed? show_toy_call call statistic must informed? minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate multiple statistics with same input data — decouple","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: run_id: Indicates order methods executed. statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score). statistic_time: requested, internal execution time indicator. p_value: p-value (available) obtained score.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate multiple statistics with same input data — decouple","text":"","code":"if (FALSE) {     inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")      mat <- readRDS(file.path(inputs_dir, \"mat.rds\"))     net <- readRDS(file.path(inputs_dir, \"net.rds\"))      decouple(         mat = mat,         network = net,         .source = \"source\",         .target = \"target\",         statistics = c(\"gsva\", \"wmean\", \"wsum\", \"ulm\", \"aucell\"),         args = list(             gsva = list(verbose = FALSE),             wmean = list(.mor = \"mor\", .likelihood = \"likelihood\"),             wsum = list(.mor = \"mor\"),             ulm = list(.mor = \"mor\")         ),         minsize = 0     ) }"},{"path":"https://saezlab.github.io/decoupleR/reference/decoupleR-package.html","id":null,"dir":"Reference","previous_headings":"","what":"decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package","title":"decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package","text":"Many methods allow us extract biological activities omics data using information prior knowledge resources, reducing dimensionality increased statistical power better interpretability. , present decoupleR, Bioconductor package containing different statistical methods extract signatures within unified framework. decoupleR allows user flexibly test method resource. incorporates methods take account sign weight network interactions. decoupleR can used omic, long features can linked biological process based prior knowledge. example, transcriptomics gene sets regulated transcription factor, phospho-proteomics phosphosites targeted kinase.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/decoupleR-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package","text":"Maintainer: Pau Badia--Mompel pau.badia@uni-heidelberg.de (ORCID) Authors: Jesús Vélez-Santiago jvelezmagic@gmail.com (ORCID) Jana Braunger jana.bc@gmx.de (ORCID) Celina Geiss celina.geiss@stud.uni-heidelberg.de (ORCID) Daniel Dimitrov daniel.dimitrov@uni-heidelberg.de (ORCID) Sophia Müller-Dott sophia.mueller-dott@uni-heidelberg.de (ORCID) Petr Taus petr.taus@ceitec.muni.cz (ORCID) Aurélien Dugourd aurelien.dugourd@bioquant.uni-heidelberg.de (ORCID) Christian H. Holland cholland2408@gmail.com (ORCID) Ricardo O. Ramirez Flores roramirezf@uni-heidelberg.de  (ORCID) Julio Saez-Rodriguez pub.saez@uni-heidelberg.de (ORCID)","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_mat_format.html","id":null,"dir":"Reference","previous_headings":"","what":"DecoupleR mat format — .decoupler_mat_format","title":"DecoupleR mat format — .decoupler_mat_format","text":"DecoupleR mat format","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_mat_format.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DecoupleR mat format — .decoupler_mat_format","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html","id":null,"dir":"Reference","previous_headings":"","what":"DecoupleR network format — .decoupler_network_format","title":"DecoupleR network format — .decoupler_network_format","text":"network passed run_ method package must contain least two attributes: .source .target. addition, methods must map corresponding metadata associated edges.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DecoupleR network format — .decoupler_network_format","text":"network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"DecoupleR network format — .decoupler_network_format","text":"attributes mapped prefixed . idea using type mapping provide flexibility different types networks, regulatory, metabolic, type. way, consider network networks long format can easily manipulated functions within tidyverse ecosystem.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":null,"dir":"Reference","previous_headings":"","what":"Pre-processing for methods that fit networks. — .fit_preprocessing","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"center true, expression values centered mean expression across samples.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"","code":".fit_preprocessing(network, mat, center, na.rm, sparse)"},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"network Tibble dataframe edges associated metadata. mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? sparse Deprecated parameter.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"named list matrices evaluate methods fit models, like .mlm_analysis(). mat: Features rows samples columns. mor_mat: Features rows columns source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) net <- rename_net(net, source, target, mor) .fit_preprocessing(net, mat, center = FALSE, na.rm = FALSE, sparse = FALSE) #> $mat #>            S01       S02       S03        S04        S05        S06        S07 #> G01 9.37095845 9.3888607 9.8951935  8.7844590 8.43144620 8.36723464 8.62351816 #> G02 8.56469817 8.2787888 8.4304691  8.8509076 8.65564788 8.18523056 8.95352336 #> G03 8.36312841 8.1333213 8.2572694 10.4142076 8.32192527 8.58182373 8.54282881 #> G04 8.63286260 8.6359504 9.7631631  8.0361226 8.78383894 9.39973683 8.58099650 #> G05 0.40426832 0.2842529 0.4600974  0.2059986 1.57572752 0.72729206 0.76817874 #> G06 0.10612452 2.6564554 0.6399949  0.3610573 0.64289931 1.30254263 0.46376759 #> G07 1.51152200 2.4404669 0.4554501  0.7581632 0.08976065 0.33584812 0.88577630 #> G08 0.09465904 1.3201133 0.7048373  0.7267048 0.27655075 1.03850610 1.09978090 #> G09 2.01842371 0.3066386 1.0351035  1.3682810 0.67928882 0.92072857 1.51270701 #> G10 0.06271410 1.7813084 0.6089264  0.4328180 0.08983289 0.72087816 0.25792144 #> G11 1.30486965 0.1719174 0.5049551  0.8113932 2.99309008 1.04311894 0.08844023 #> G12 2.28664539 1.2146747 1.7170087  1.4441013 0.28488295 0.09018639 0.12089654 #>           S08       S09       S10         S11        S12       S13         S14 #> G01 9.1943289 9.1317387 8.1881930 9.493625067 8.00006288 0.4138688 0.007762034 #> G02 8.6119969 9.4592140 8.1191610 9.470435741 9.12288964 1.1133860 0.800282178 #> G03 8.2171398 8.0799826 8.0250926 8.124702386 9.43985574 0.4809928 0.533492330 #> G04 8.1827567 8.6532043 8.1080727 8.996639135 9.09711377 0.4331690 1.287675246 #> G05 0.9333463 1.2009654 0.4854352 0.001822614 0.11731956 8.6968626 8.175525870 #> G06 0.8217731 1.0447511 0.5042171 0.428258881 1.20149840 9.0563684 9.071782384 #> G07 1.3921164 1.0032086 1.6610991 0.613671606 0.46972958 8.0406985 8.163206882 #> G08 0.4761739 1.8484819 0.3823337 2.024677845 0.05246948 9.5515448 8.362738416 #> G09 0.6503486 0.6667734 0.5126503 1.224747950 0.08610730 1.1671695 0.590013548 #> G10 1.3911105 0.1055138 2.7018910 0.179516441 0.88767902 0.2736457 1.432421928 #> G11 1.1107889 0.4222559 1.3621162 0.567620594 0.44468400 0.4678453 0.992692511 #> G12 0.8607926 0.1223502 0.1372562 0.492877354 0.02944488 1.2382523 0.454650298 #>             S15       S16       S17         S18       S19       S20         S21 #> G01 0.084898059 0.1514559 0.2526117  1.37686160 0.1320880 0.6585034  0.72921728 #> G02 0.895565582 0.5841090 1.2940025  1.15085557 1.4767874 1.2502366  0.99806891 #> G03 0.229778139 0.3688067 0.9591704  0.70582139 0.2170302 0.2717637  1.25848166 #> G04 0.836619068 0.2946543 1.0857749  1.05405578 1.2836022 0.9479520  1.24886369 #> G05 9.745055861 8.2792594 8.4037749  8.64574372 8.3856679 9.2015824  9.38063705 #> G06 9.689458921 9.3362367 8.5864875  8.18537797 8.3515129 8.4661161 10.04996069 #> G07 8.864777979 8.7007488 9.8152284  9.20122205 8.5217961 8.2693514  9.01687283 #> G08 8.150775989 8.5541966 8.1288214 10.03697217 9.0681312 8.3909654  8.02671746 #> G09 1.449007130 0.8363066 2.0009292  0.10777474 0.4283659 1.3487070  0.70360778 #> G10 0.643008700 1.5945882 0.3337772  0.08410810 0.1740182 0.0227647  0.97138523 #> G11 0.483193864 0.2049586 1.1713251  0.49561964 0.5156677 0.2442259  1.09615624 #> G12 0.006355626 0.3450880 2.0595392  0.03741519 0.2343653 0.9423717  0.04905045 #>           S22         S23        S24 #> G01 1.1984959  0.05399674 0.47039340 #> G02 0.1900190  1.06477321 1.24267027 #> G03 1.2977059  0.81319504 1.38157546 #> G04 1.0338737  0.19081647 1.20445894 #> G05 8.7384408 10.69992981 8.82407396 #> G06 8.0465639  8.06096664 9.66262940 #> G07 9.0175961  8.57375170 8.56930634 #> G08 8.3832840  8.04580358 8.63551382 #> G09 0.8727554  0.15741254 0.04372201 #> G10 0.9695450  0.43156537 0.34801230 #> G11 0.3838467  0.39654974 2.45959355 #> G12 1.8515557  1.30997823 0.81838032 #>  #> $mor_mat #>      T1  T2   T3 #> G01 1.0 0.0  0.0 #> G02 1.0 0.0  0.0 #> G03 0.7 0.0  0.0 #> G04 0.0 0.0  0.0 #> G05 0.0 0.0  0.0 #> G06 0.0 1.0 -0.5 #> G07 0.0 0.5 -3.0 #> G08 0.0 1.0 -1.0 #> G09 0.0 0.0  0.0 #> G10 0.0 0.0  0.0 #> G11 0.0 0.0  1.0 #> G12 0.0 0.0  0.0 #>"},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract sets — extract_sets","title":"Extract sets — extract_sets","text":"Extracts feature sets renamed network (see rename_net).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract sets — extract_sets","text":"","code":"extract_sets(network)"},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract sets — extract_sets","text":"network Tibble dataframe edges associated metadata.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract sets — extract_sets","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) net <- rename_net(net, source, target, mor) extract_sets(net) #> $T1 #> [1] \"G01\" \"G02\" \"G03\" #>  #> $T2 #> [1] \"G06\" \"G07\" \"G08\" #>  #> $T3 #> [1] \"G06\" \"G07\" \"G08\" \"G11\" #>"},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter sources with minsize targets — filt_minsize","title":"Filter sources with minsize targets — filt_minsize","text":"Filter sources net less minsize targets","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter sources with minsize targets — filt_minsize","text":"","code":"filt_minsize(mat_f_names, network, minsize = 5)"},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter sources with minsize targets — filt_minsize","text":"mat_f_names Feature names mat. network Tibble dataframe edges associated metadata. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter sources with minsize targets — filt_minsize","text":"Filtered network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter sources with minsize targets — filt_minsize","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) net <- rename_net(net, source, target, mor) filt_minsize(rownames(mat), net, minsize = 4) #> # A tibble: 4 × 4 #>   source target   mor likelihood #>   <chr>  <chr>  <dbl>      <dbl> #> 1 T3     G06     -0.5          1 #> 2 T3     G07     -3            1 #> 3 T3     G08     -1            1 #> 4 T3     G11      1            1"},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":null,"dir":"Reference","previous_headings":"","what":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"CollecTRI gene regulatory network. Wrapper access CollecTRI gene regulatory network. CollecTRI comprehensive resource containing curated collection transcription factors (TFs) target genes. expansion DoRothEA. interaction weighted mode regulation (either positive negative).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"","code":"get_collectri(organism = \"human\", split_complexes = FALSE, ...)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"organism organism use. human, mouse rat available. split_complexes Whether split complexes subunits. default complexes kept . ... Ignored.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"","code":"collectri <- get_collectri(organism='human', split_complexes=FALSE)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":null,"dir":"Reference","previous_headings":"","what":"DoRothEA gene regulatory network. — get_dorothea","title":"DoRothEA gene regulatory network. — get_dorothea","text":"Wrapper access DoRothEA gene regulatory network. DoRothEA comprehensive resource containing curated collection transcription factors (TFs) target genes. interaction weighted mode regulation (either positive negative) confidence level","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"DoRothEA gene regulatory network. — get_dorothea","text":"","code":"get_dorothea(   organism = \"human\",   levels = c(\"A\", \"B\", \"C\"),   weight_dict = list(A = 1, B = 2, C = 3, D = 4) )"},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DoRothEA gene regulatory network. — get_dorothea","text":"organism organism use. human, mouse rat available. levels List confidence levels return. Goes D, confident D less. weight_dict Dictionary values divide mode regulation (-1 1), one confidence level. Bigger values generate weights close zero.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"DoRothEA gene regulatory network. — get_dorothea","text":"","code":"dorothea <- get_dorothea(organism='human', levels=c('A', 'B'))"},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":null,"dir":"Reference","previous_headings":"","what":"OmniPath kinase-substrate network — get_ksn_omnipath","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"Retrieve ready use, curated kinase-substrate Network OmniPath database.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"","code":"get_ksn_omnipath(...)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"... Passed OmnipathR::import_omnipath_enzsub.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"Import enzyme-PTM network OmniPath, filter anything phospho dephosphorilation. format columns use decoupleR functions.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":null,"dir":"Reference","previous_headings":"","what":"Complete a data frame with missing combinations of data — get_profile_of","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"Turns implicit missing values explicit missing values. wrapper around expand(), dplyr::full_join() replace_na() useful completing missing combinations data.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"","code":"get_profile_of(data, sources, values_fill = NA)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"data data frame. sources named vector list values expand get profile. values_fill Optionally, (scalar) value specifies value filled missing. can named list want apply different fill values different value columns.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"data frame expanded grid values passed sources filled specified fill argument.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"","code":"if (FALSE) { library(dplyr, warn.conflicts = FALSE) df <- tibble(     group = c(1:2, 1),     item_id = c(1:2, 2),     item_name = c(\"a\", \"b\", \"b\"),     value1 = 1:3,     value2 = 4:6 )  to_get_profile <- list(group = c(1, 2, 3), item_id = c(1, 2))  # This will add the combinations of group 3 with the id of the items df %>% get_profile_of(sources = to_get_profile)  # You can also choose to fill in missing values  # This only fill with \"Unknown\" the NA values of the column item_name df %>% get_profile_of(     sources = to_get_profile,     values_fill = list(item_name = \"Unknown\") )  # Replace all NAs with \"Unkwnon\" df %>% get_profile_of(sources = to_get_profile, values_fill = \"Unknown\") }"},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":null,"dir":"Reference","previous_headings":"","what":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"Wrapper access PROGENy model gene weights. pathway defined collection target genes, interaction associated p-value weight. top significant interactions per pathway returned.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"","code":"get_progeny(organism = \"human\", top = 500)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"organism organism use. human mouse available. top Number genes per pathway return.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"","code":"progeny <- get_progeny(organism='human', top=500)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"Wrapper access resources inside Omnipath. wrapper allows easily query different prior knowledge resources. check available resources run decoupleR::show_resources(). information visit official website Omnipath.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"","code":"get_resource(name, organism = \"human\", ...)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"name Name resource query. organism Organism name NCBI Taxonomy ID. ... Passed OmnipathR::import_omnipath_annotations.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"","code":"df <- decoupleR::get_resource('SIGNOR')"},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a toy mat and network. — get_toy_data","title":"Generate a toy mat and network. — get_toy_data","text":"Generate toy mat network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a toy mat and network. — get_toy_data","text":"","code":"get_toy_data(n_samples = 24, seed = 42)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a toy mat and network. — get_toy_data","text":"n_samples Number samples simulate. seed single value, interpreted integer, NULL random number generation.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a toy mat and network. — get_toy_data","text":"List containing mat network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a toy mat and network. — get_toy_data","text":"","code":"data <- get_toy_data() mat <- data$mat network <- data$network"},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":null,"dir":"Reference","previous_headings":"","what":"Intersect network target features with input matrix. — intersect_regulons","title":"Intersect network target features with input matrix. — intersect_regulons","text":"Keep edges target features belong input matrix.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Intersect network target features with input matrix. — intersect_regulons","text":"","code":"intersect_regulons(mat, network, .source, .target, minsize)"},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Intersect network target features with input matrix. — intersect_regulons","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. minsize Minimum number targets per source allowed.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Intersect network target features with input matrix. — intersect_regulons","text":"Filtered tibble.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Intersect network target features with input matrix. — intersect_regulons","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) intersect_regulons(mat, net, source, target, minsize=4) #> # A tibble: 4 × 3 #> # Groups:   source [1] #>   source target   mor #>   <chr>  <chr>  <dbl> #> 1 T3     G06     -0.5 #> 2 T3     G07     -3   #> 3 T3     G08     -1   #> 4 T3     G11      1"},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"Pipe object forward function call expression.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pipe operator — %>%","text":"","code":"c(1, 2, 3) %>% sum() #> [1] 6"},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":null,"dir":"Reference","previous_headings":"","what":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"Generates kind table rows come id_cols, columns names_from values values_from.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"","code":"pivot_wider_profile(   data,   id_cols,   names_from,   values_from,   values_fill = NA,   to_matrix = FALSE,   to_sparse = FALSE,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"data data frame pivot. id_cols <tidy-select> set columns uniquely identify observation. Typically used redundant variables, .e. variables whose values perfectly correlated existing variables. Defaults columns data except columns specified names_from values_from. tidyselect expression supplied, evaluated data removing columns specified names_from values_from. names_from, values_from <tidy-select> pair arguments describing column (columns) get name output column (names_from), column (columns) get cell values (values_from). values_from contains multiple values, value added front output column. values_fill Optionally, (scalar) value specifies value filled missing. can named list want apply different fill values different value columns. to_matrix Logical value indicating result matrix. Parameter ignored case sparse TRUE. to_sparse Logical value indicating whether resulting matrix sparse . ... Additional arguments passed methods.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"\"widened\" data; increasing number columns decreasing number rows.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"current state function, ensure operation, id_cols parameter single selector.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"","code":"if (FALSE) { df <- tibble::tibble(     tf = c(\"tf_1\", \"tf_1\", \"tf_2\", \"tf_2\"),     gene = c(\"gene_1\", \"gene_2\", \"gene_1\", \"gene_2\"),     mor = c(1, -1, 1, -1) )  # Return a tibble pivot_wider_profile(     data = df,     id_cols = tf,     names_from = gene,     values_from = mor )  # Return a matrix pivot_wider_profile(     data = df,     id_cols = tf,     names_from = gene,     values_from = mor,     to_matrix = TRUE ) # Return a sparse Matrix of class \"dgCMatrix\" pivot_wider_profile(     data = df,     id_cols = tf,     names_from = gene,     values_from = mor,     to_sparse = TRUE ) }"},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Randomize matrix — randomize_matrix","title":"Randomize matrix — randomize_matrix","text":"Utility function used functions require permutations expression matrix","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Randomize matrix — randomize_matrix","text":"","code":"randomize_matrix(mat, randomize_type = c(\"rows\", \"cols_independently\"))"},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Randomize matrix — randomize_matrix","text":"mat Matrix randomize. randomize_type randomize.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Randomize matrix — randomize_matrix","text":"Randomized matrix","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Randomize matrix — randomize_matrix","text":"","code":"if (FALSE) { mat <- matrix(seq_len(9), ncol = 3) mat  set.seed(42) randomize_matrix(mat, randomize_type = \"rows\")  set.seed(42) randomize_matrix(mat, randomize_type = \"cols_independently\") }"},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":null,"dir":"Reference","previous_headings":"","what":"Rename network — rename_net","title":"Rename network — rename_net","text":"Renames given network column names: .source, .target, .mor, .mor provided, function sets default values.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rename network — rename_net","text":"","code":"rename_net(   network,   .source,   .target,   .mor = NULL,   .likelihood = NULL,   def_mor = 1 )"},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rename network — rename_net","text":"network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. def_mor Default value .mor provided.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rename network — rename_net","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) rename_net(net, source, target, mor) #> # A tibble: 10 × 4 #>    source target   mor likelihood #>    <chr>  <chr>  <dbl>      <dbl> #>  1 T1     G01      1            1 #>  2 T1     G02      1            1 #>  3 T1     G03      0.7          1 #>  4 T2     G06      1            1 #>  5 T2     G07      0.5          1 #>  6 T2     G08      1            1 #>  7 T3     G06     -0.5          1 #>  8 T3     G07     -3            1 #>  9 T3     G08     -1            1 #> 10 T3     G11      1            1"},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":null,"dir":"Reference","previous_headings":"","what":"AUCell — run_aucell","title":"AUCell — run_aucell","text":"Calculates regulatory activities using AUCell.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AUCell — run_aucell","text":"","code":"run_aucell(   mat,   network,   .source = source,   .target = target,   aucMaxRank = ceiling(0.05 * nrow(rankings)),   nproc = availableCores(),   seed = 42,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AUCell — run_aucell","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. aucMaxRank Threshold calculate AUC. nproc Number cores use computation. seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"AUCell — run_aucell","text":"AUCell (Aibar et al., 2017) uses Area Curve (AUC) calculate whether set targets enriched within molecular readouts sample. , AUCell first ranks molecular features sample highest lowest value, resolving ties randomly. , AUC can calculated using default top 5% molecular features ranking. Therefore, metric, aucell, represents proportion abundant molecular features target set, relative abundance value compared features within sample. Aibar S. et al. (2017) Scenic: single-cell regulatory network inference clustering. Nat. Methods, 14, 1083–1086.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"AUCell — run_aucell","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_aucell(mat, net, minsize=0, nproc=1, aucMaxRank=3) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 aucell    T1     S01       0.667 #>  2 aucell    T1     S02       0.667 #>  3 aucell    T1     S03       0.667 #>  4 aucell    T1     S04       1     #>  5 aucell    T1     S05       0.333 #>  6 aucell    T1     S06       0.333 #>  7 aucell    T1     S07       1     #>  8 aucell    T1     S08       1     #>  9 aucell    T1     S09       1     #> 10 aucell    T1     S10       1     #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":null,"dir":"Reference","previous_headings":"","what":"Consensus score between methods — run_consensus","title":"Consensus score between methods — run_consensus","text":"Function generate consensus score methods result decouple function.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Consensus score between methods — run_consensus","text":"","code":"run_consensus(df, include_time = FALSE, seed = NULL)"},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Consensus score between methods — run_consensus","text":"df decouple data frame result include_time time per statistic evaluated informed? seed Deprecated parameter.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Consensus score between methods — run_consensus","text":"Updated tibble computed consensus score methods","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Consensus score between methods — run_consensus","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  results <- decouple(    mat = mat,    network = net,    .source = \"source\",    .target = \"target\",    statistics = c(\"wmean\", \"ulm\"),    args = list(             wmean = list(.mor = \"mor\", .likelihood = \"likelihood\"),             ulm = list(.mor = \"mor\", .likelihood = \"likelihood\")         ),    consensus_score = FALSE,    minsize = 0    ) run_consensus(results) #> # A tibble: 72 × 6 #>    condition run_id statistic source  score p_value #>    <chr>      <dbl> <chr>     <chr>   <dbl>   <dbl> #>  1 S01            3 consensus T1      1.21    0.227 #>  2 S01            3 consensus T2     -0.327   0.744 #>  3 S01            3 consensus T3     -0.217   0.828 #>  4 S02            3 consensus T1      1.21    0.226 #>  5 S02            3 consensus T2     -0.267   0.789 #>  6 S02            3 consensus T3     -0.289   0.773 #>  7 S03            3 consensus T1      1.20    0.229 #>  8 S03            3 consensus T2     -0.320   0.749 #>  9 S03            3 consensus T3     -0.196   0.845 #> 10 S04            3 consensus T1      1.21    0.228 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":null,"dir":"Reference","previous_headings":"","what":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"Calculates regulatory activities using FGSEA.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"","code":"run_fgsea(   mat,   network,   .source = source,   .target = target,   times = 100,   nproc = availableCores(),   seed = 42,   minsize = 5,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. times many permutations ? nproc Number cores use computation. seed single value, interpreted integer, NULL. minsize Integer indicating minimum number targets per source. ... Arguments passed fgsea::fgseaMultilevel sampleSize size random set genes turn size = pathwaySize minSize Minimal size gene set test. pathways threshold excluded. maxSize Maximal size gene set test. pathways threshold excluded. eps parameter sets boundary calculating p value. scoreType parameter defines GSEA score type. Possible options (\"std\", \"pos\", \"neg\"). default (\"std\") enrichment score computed original GSEA. \"pos\" \"neg\" score types intended used one-tailed tests (.e. one interested positive (\"pos\") negateive (\"neg\") enrichment). gseaParam GSEA parameter value, gene-level statis raised power `gseaParam` calculation GSEA enrichment scores. BPPARAM Parallelization parameter used bplapply. Can used specify cluster run. initialized explicitly setting `nproc` default value `bpparam()` used. absEps deprecated, use `eps` parameter instead","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"GSEA (Aravind et al., 2005) starts transforming input molecular readouts mat ranks sample. , enrichment score fgsea calculated walking list features, increasing running-sum statistic feature target feature set encountered decreasing . final score maximum deviation zero encountered random walk. Finally, normalized score norm_fgsea, can obtained computing z-score estimate compared null distribution obtained N random permutations. used implementation taken package fgsea (Korotkevich et al., 2021). Aravind S. et al. (2005) Gene set enrichment analysis: knowledge-based approach interpreting genome-wide expression profiles. PNAS. 102, 43. Korotkevich G. et al. (2021) Fast gene set enrichment analysis. bioRxiv. DOI: https://doi.org/10.1101/060012.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_fgsea(mat, net, minsize=0, nproc=1) #>    |                                                                               |                                                                      |   0%   |                                                                               |======================================================================| 100% #>  #>    |                                                                               |                                                                      | 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                                                       |===================================                                   |  50%   |                                                                               |======================================================================| 100% #>  #> # A tibble: 144 × 5 #>    statistic  source condition   score p_value #>    <chr>      <chr>  <chr>       <dbl>   <dbl> #>  1 fgsea      T1     S01         0.889  0.0755 #>  2 norm_fgsea T1     S01         1.24   0.0755 #>  3 fgsea      T2     S01        -0.667  0.548  #>  4 norm_fgsea T2     S01        -1.11   0.548  #>  5 fgsea      T3     S01        -0.75   0.01   #>  6 norm_fgsea T3     S01       Inf      0.01   #>  7 fgsea      T1     S02         0.889  0.0764 #>  8 norm_fgsea T1     S02         1.29   0.0764 #>  9 fgsea      T2     S02         0      0.977  #> 10 norm_fgsea T2     S02         0      0.977  #> # ℹ 134 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":null,"dir":"Reference","previous_headings":"","what":"Gene Set Variation Analysis (GSVA) — run_gsva","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"Calculates regulatory activities using GSVA.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"","code":"run_gsva(   mat,   network,   .source = source,   .target = target,   verbose = FALSE,   method = c(\"gsva\", \"plage\", \"ssgsea\", \"zscore\"),   minsize = 5L,   maxsize = Inf,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. verbose Gives information calculation step. Default: FALSE. method Method employ estimation gene-set enrichment. scores per sample. default set gsva (Hänzelmann et al, 2013). available methods \"plage\", \"ssgsea\" \"zscore\". Read manual GSVA::gsva. minsize Integer indicating minimum number targets per source. Must greater 0. maxsize Integer indicating maximum number targets per source. ... Arguments passed GSVA::gsvaParam, GSVA::ssgseaParam assay name assay use case exprData multi-assay container, otherwise ignored.  default, first assay used. annotation name Bioconductor annotation package gene identifiers occurring row names expression data matrix.  can used map gene identifiers occurring gene sets provided GeneSetCollection.  default gene identifiers used expression data matrix gene sets matched directly. kcdf Character vector length 1 denoting kernel use non-parametric estimation cumulative distribution function expression levels across samples.  default, kcdf=\"Gaussian\" suitable input expression values continuous, microarray fluorescent units logarithmic scale, RNA-seq log-CPMs, log-RPKMs log-TPMs.  input expression values integer counts, derived RNA-seq experiments, argument set kcdf=\"Poisson\". tau Numeric vector length 1.  exponent defining weight tail random walk performed GSVA (Hänzelmann et al., 2013) method.  default value 1 described paper. maxDiff Logical vector length 1 offers two approaches calculate enrichment statistic (ES) KS random walk statistic. FALSE: ES calculated maximum distance random walk 0. TRUE (default): ES calculated magnitude difference largest positive negative random walk deviations. absRanking Logical vector length 1 used maxDiff=TRUE. absRanking=FALSE (default) modified Kuiper statistic used calculate enrichment scores, taking magnitude difference largest positive negative random walk deviations. absRanking=TRUE original Kuiper statistic sums largest positive negative random walk deviations, used. latter case, gene sets genes enriched either extreme (high low) regarded ’highly’ activated. alpha Numeric vector length 1.  exponent defining weight tail random walk performed ssGSEA (Barbie et al., 2009) method.  default value 0.25 described paper. normalize Logical vector length 1; TRUE  runs ssGSEA method Barbie et al. (2009) normalizing scores absolute difference minimum maximum, described paper. Otherwise last normalization step skipped.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"GSVA (Hänzelmann et al., 2013) starts transforming input molecular readouts mat readout-level statistic using Gaussian kernel estimation cumulative density function. , readout-level statistics ranked per sample normalized -weight two tails rank distribution. Afterwards, enrichment score gsva calculated using running sum statistic normalized subtracting largest negative estimate largest positive one. Hänzelmann S. et al. (2013) GSVA: gene set variation analysis microarray RNA-seq data. BMC Bioinformatics, 14, 7.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_gsva(mat, net, minsize=1, verbose = FALSE) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 gsva      T1     S01       0.222 #>  2 gsva      T1     S02       0.556 #>  3 gsva      T1     S03       0.667 #>  4 gsva      T1     S04       0.778 #>  5 gsva      T1     S05       0.556 #>  6 gsva      T1     S06       0.667 #>  7 gsva      T1     S07       0.667 #>  8 gsva      T1     S08       0.667 #>  9 gsva      T1     S09       0.889 #> 10 gsva      T1     S10       0.444 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":null,"dir":"Reference","previous_headings":"","what":"Multivariate Decision Trees (MDT) — run_mdt","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"Calculates regulatory activities using MDT.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"","code":"run_mdt(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   trees = 10,   min_n = 20,   nproc = availableCores(),   seed = 42,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? trees integer number trees contained ensemble. min_n integer minimum number data points node required node split . nproc Number cores use computation. seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"MDT fits multivariate regression random forest sample, observed molecular readouts mat response variable regulator weights net covariates. Target features associated weight set zero. obtained feature importances fitted model activities mdt regulators net.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_mdt(mat, net, minsize=0) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 mdt       T1     S01           0 #>  2 mdt       T1     S02           0 #>  3 mdt       T1     S03           0 #>  4 mdt       T1     S04           0 #>  5 mdt       T1     S05           0 #>  6 mdt       T1     S06           0 #>  7 mdt       T1     S07           0 #>  8 mdt       T1     S08           0 #>  9 mdt       T1     S09           0 #> 10 mdt       T1     S10           0 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":null,"dir":"Reference","previous_headings":"","what":"Multivariate Linear Model (MLM) — run_mlm","title":"Multivariate Linear Model (MLM) — run_mlm","text":"Calculates regulatory activities using MLM.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Multivariate Linear Model (MLM) — run_mlm","text":"","code":"run_mlm(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Multivariate Linear Model (MLM) — run_mlm","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Multivariate Linear Model (MLM) — run_mlm","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Multivariate Linear Model (MLM) — run_mlm","text":"MLM fits multivariate linear model sample, observed molecular readouts mat response variable regulator weights net covariates. Target features associated weight set zero. obtained t-values fitted model activities (mlm) regulators net.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Multivariate Linear Model (MLM) — run_mlm","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_mlm(mat, net, minsize=0) #> # A tibble: 72 × 5 #>    statistic source condition   score p_value #>    <chr>     <chr>  <chr>       <dbl>   <dbl> #>  1 mlm       T1     S01        3.52   0.00781 #>  2 mlm       T2     S01       -1.13   0.290   #>  3 mlm       T3     S01       -0.247  0.811   #>  4 mlm       T1     S02        3.48   0.00831 #>  5 mlm       T2     S02       -0.213  0.837   #>  6 mlm       T3     S02       -0.353  0.733   #>  7 mlm       T1     S03        3.15   0.0135  #>  8 mlm       T2     S03       -0.638  0.541   #>  9 mlm       T3     S03        0.0749 0.942   #> 10 mlm       T1     S04        3.82   0.00512 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":null,"dir":"Reference","previous_headings":"","what":"Over Representation Analysis (ORA) — run_ora","title":"Over Representation Analysis (ORA) — run_ora","text":"Calculates regulatory activities using ORA.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Over Representation Analysis (ORA) — run_ora","text":"","code":"run_ora(   mat,   network,   .source = source,   .target = target,   n_up = ceiling(0.05 * nrow(mat)),   n_bottom = 0,   n_background = 20000,   with_ties = TRUE,   seed = 42,   minsize = 5,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Over Representation Analysis (ORA) — run_ora","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. n_up Integer indicating number top targets slice mat. n_bottom Integer indicating number bottom targets slice mat. n_background Integer indicating background size sliced targets. specified number background targets determined total number unique targets union mat network. with_ties ties kept together? default, TRUE, may return rows request. Use FALSE ignore ties, return first n rows. seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source. ... Arguments passed stats::fisher.test workspace integer specifying size workspace     used network algorithm.  units 4 bytes.  used     non-simulated p-values larger \\(2 \\times 2\\) tables.     Since R version 3.5.0, also increases internal stack size     allows larger problems solved, however sometimes needing     hours.  cases, simulate.p.values=TRUE may     reasonable. hybrid logical. used larger \\(2 \\times 2\\)     tables, cases indicates whether exact probabilities     (default) hybrid approximation thereof computed. hybridPars numeric vector length 3, default describing     “Cochran's conditions” validity chisquare     approximation, see ‘Details’. control list named components low level algorithm     control.  present one used \"mult\", positive     integer \\(\\ge 2\\) default 30 used larger     \\(2 \\times 2\\) tables.  says many times much     space allocated paths keys: see file     fexact.c sources package. hypothesized odds ratio.  used     \\(2 \\times 2\\) case. alternative indicates alternative hypothesis must     one \"two.sided\", \"greater\" \"less\".     can specify just initial letter.  used     \\(2 \\times 2\\) case. conf.int logical indicating confidence interval     odds ratio \\(2 \\times 2\\) table     computed (returned). conf.level confidence level returned confidence     interval.  used \\(2 \\times 2\\) case     conf.int = TRUE. simulate.p.value logical indicating whether compute     p-values Monte Carlo simulation, larger \\(2 \\times       2\\) tables. B integer specifying number replicates used     Monte Carlo test.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Over Representation Analysis (ORA) — run_ora","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Over Representation Analysis (ORA) — run_ora","text":"ORA measures overlap target feature set list altered molecular features mat. altered molecular features can selected top bottom molecular readout distribution, default top 5% positive values. , contingency table build one-tailed Fisher’s exact test computed determine regulator’s set features -represented selected features data. resulting score, ora, minus log10 obtained p-value.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Over Representation Analysis (ORA) — run_ora","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_ora(mat, net, minsize=0) #> # A tibble: 72 × 5 #>    statistic source condition score  p_value #>    <chr>     <chr>  <chr>     <dbl>    <dbl> #>  1 ora       T1     S01        3.82 0.000150 #>  2 ora       T1     S02        3.82 0.000150 #>  3 ora       T1     S03        3.82 0.000150 #>  4 ora       T1     S04        3.82 0.000150 #>  5 ora       T1     S05        0    1        #>  6 ora       T1     S06        0    1        #>  7 ora       T1     S07        3.82 0.000150 #>  8 ora       T1     S08        3.82 0.000150 #>  9 ora       T1     S09        3.82 0.000150 #> 10 ora       T1     S10        3.82 0.000150 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":null,"dir":"Reference","previous_headings":"","what":"Univariate Decision Tree (UDT) — run_udt","title":"Univariate Decision Tree (UDT) — run_udt","text":"Calculates regulatory activities using UDT.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Univariate Decision Tree (UDT) — run_udt","text":"","code":"run_udt(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   min_n = 20,   seed = 42,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Univariate Decision Tree (UDT) — run_udt","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? min_n integer minimum number data points node required node split . seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Univariate Decision Tree (UDT) — run_udt","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Univariate Decision Tree (UDT) — run_udt","text":"UDT fits single regression decision tree sample regulator, observed molecular readouts mat response variable regulator weights net explanatory one. Target features associated weight set zero. obtained feature importance fitted model activity udt given regulator.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Univariate Decision Tree (UDT) — run_udt","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_udt(mat, net, minsize=0) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 udt       T1     S01           0 #>  2 udt       T1     S02           0 #>  3 udt       T1     S03           0 #>  4 udt       T1     S04           0 #>  5 udt       T1     S05           0 #>  6 udt       T1     S06           0 #>  7 udt       T1     S07           0 #>  8 udt       T1     S08           0 #>  9 udt       T1     S09           0 #> 10 udt       T1     S10           0 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":null,"dir":"Reference","previous_headings":"","what":"Univariate Linear Model (ULM) — run_ulm","title":"Univariate Linear Model (ULM) — run_ulm","text":"Calculates regulatory activities using ULM.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Univariate Linear Model (ULM) — run_ulm","text":"","code":"run_ulm(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   minsize = 5L )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Univariate Linear Model (ULM) — run_ulm","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Univariate Linear Model (ULM) — run_ulm","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Univariate Linear Model (ULM) — run_ulm","text":"ULM fits linear model sample regulator, observed molecular readouts mat response variable regulator weights net explanatory one. Target features associated weight set zero. obtained t-value fitted model activity ulm given regulator.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Univariate Linear Model (ULM) — run_ulm","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_ulm(mat, net, minsize=0) #> # A tibble: 72 × 5 #>    statistic source condition score  p_value #>    <chr>     <chr>  <chr>     <dbl>    <dbl> #>  1 ulm       T1     S01        4.21 0.00180  #>  2 ulm       T1     S02        4.07 0.00224  #>  3 ulm       T1     S03        3.85 0.00319  #>  4 ulm       T1     S04        4.60 0.000979 #>  5 ulm       T1     S05        3.90 0.00298  #>  6 ulm       T1     S06        3.66 0.00442  #>  7 ulm       T1     S07        4.31 0.00153  #>  8 ulm       T1     S08        4.65 0.000902 #>  9 ulm       T1     S09        4.49 0.00117  #> 10 ulm       T1     S10        4.07 0.00225  #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":null,"dir":"Reference","previous_headings":"","what":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"Calculates regulatory activities using VIPER.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"","code":"run_viper(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   verbose = FALSE,   minsize = 5,   pleiotropy = TRUE,   eset.filter = FALSE,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. verbose Logical, whether progression messages printed terminal. minsize Integer indicating minimum number targets per source. pleiotropy Logical, whether correction pleiotropic regulation performed. eset.filter Logical, whether dataset limited genes represented interactome. ... Arguments passed viper::viper dnull Numeric matrix null model, usually generated nullTtest nes Logical, whether enrichment score reported normalized method Character string indicating method computing single samples signature, either scale, rank, mad, ttest none bootstraps Integer indicating number bootstraps iterations perform. scale method implemented bootstraps. adaptive.size Logical, whether weighting scores taken account computing regulon size pleiotropyArgs list 5 numbers pleotropy correction indicating: regulators p-value threshold, pleiotropic interaction p-value threshold, minimum number targets overlap pleiotropic regulators, penalty pleiotropic interactions method computing pleiotropy, either absolute adaptive cores Integer indicating number cores use (1 Windows-based systems)","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"VIPER (Alvarez et al., 2016) estimates biological activities performing three-tailed enrichment score calculation. information check supplementary information decoupler manuscript original publication. Alvarez M.J.et al. (2016) Functional characterization somatic mutations cancer using network-based inference protein activity. Nat. Genet., 48, 838–847.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_viper(mat, net, minsize=0, verbose = FALSE) #> # A tibble: 72 × 5 #>    statistic source condition score p_value #>    <chr>     <chr>  <chr>     <dbl>   <dbl> #>  1 viper     T1     S01        1.45  0.147  #>  2 viper     T1     S02        1.45  0.147  #>  3 viper     T1     S03        1.45  0.147  #>  4 viper     T1     S04        1.84  0.0662 #>  5 viper     T1     S05        1.22  0.224  #>  6 viper     T1     S06        1.25  0.209  #>  7 viper     T1     S07        1.62  0.106  #>  8 viper     T1     S08        1.76  0.0783 #>  9 viper     T1     S09        1.62  0.106  #> 10 viper     T1     S10        1.62  0.106  #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Weighted Mean (WMEAN) — run_wmean","title":"Weighted Mean (WMEAN) — run_wmean","text":"Calculates regulatory activities using WMEAN.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Weighted Mean (WMEAN) — run_wmean","text":"","code":"run_wmean(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   times = 100,   seed = 42,   sparse = TRUE,   randomize_type = \"rows\",   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Weighted Mean (WMEAN) — run_wmean","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. times many permutations ? seed single value, interpreted integer, NULL random number generation. sparse matrices used calculation sparse? randomize_type randomize expression matrix. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Weighted Mean (WMEAN) — run_wmean","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score). p_value: p-value score method.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Weighted Mean (WMEAN) — run_wmean","text":"WMEAN infers regulator activities first multiplying target feature associated weight summed enrichment score wmean. Furthermore, permutations random target features can performed obtain null distribution can used compute z-score norm_wmean, corrected estimate corr_wmean multiplying wmean minus log10 obtained empirical p-value.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Weighted Mean (WMEAN) — run_wmean","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_wmean(mat, net, minsize=0) #> # A tibble: 216 × 5 #>    statistic  source condition score p_value #>    <chr>      <chr>  <chr>     <dbl>   <dbl> #>  1 corr_wmean T1     S01        15.0    0.02 #>  2 corr_wmean T1     S02        14.7    0.02 #>  3 corr_wmean T1     S03        15.2    0.02 #>  4 corr_wmean T1     S04        15.7    0.02 #>  5 corr_wmean T1     S05        14.4    0.02 #>  6 corr_wmean T1     S06        14.2    0.02 #>  7 corr_wmean T1     S07        14.8    0.02 #>  8 corr_wmean T1     S08        14.8    0.02 #>  9 corr_wmean T1     S09        15.3    0.02 #> 10 corr_wmean T1     S10        13.8    0.02 #> # ℹ 206 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":null,"dir":"Reference","previous_headings":"","what":"Weighted Sum (WSUM) — run_wsum","title":"Weighted Sum (WSUM) — run_wsum","text":"Calculates regulatory activities using WSUM.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Weighted Sum (WSUM) — run_wsum","text":"","code":"run_wsum(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   times = 100,   seed = 42,   sparse = TRUE,   randomize_type = \"rows\",   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Weighted Sum (WSUM) — run_wsum","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. times many permutations ? seed single value, interpreted integer, NULL random number generation. sparse matrices used calculation sparse? randomize_type randomize expression matrix. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Weighted Sum (WSUM) — run_wsum","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score). p_value: p-value score method.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Weighted Sum (WSUM) — run_wsum","text":"WSUM infers regulator activities first multiplying target feature associated weight summed enrichment score wsum. Furthermore, permutations random target features can performed obtain null distribution can used compute z-score norm_wsum, corrected estimate corr_wsum multiplying wsum minus log10 obtained empirical p-value.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Weighted Sum (WSUM) — run_wsum","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_wsum(mat, net, minsize=0) #> # A tibble: 216 × 5 #>    statistic source condition score p_value #>    <chr>     <chr>  <chr>     <dbl>   <dbl> #>  1 corr_wsum T1     S01        40.4    0.02 #>  2 corr_wsum T1     S02        39.7    0.02 #>  3 corr_wsum T1     S03        41.0    0.02 #>  4 corr_wsum T1     S04        42.3    0.02 #>  5 corr_wsum T1     S05        38.9    0.02 #>  6 corr_wsum T1     S06        38.3    0.02 #>  7 corr_wsum T1     S07        40.0    0.02 #>  8 corr_wsum T1     S08        40.0    0.02 #>  9 corr_wsum T1     S09        41.2    0.02 #> 10 corr_wsum T1     S10        37.2    0.02 #> # ℹ 206 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/show_methods.html","id":null,"dir":"Reference","previous_headings":"","what":"Show methods — show_methods","title":"Show methods — show_methods","text":"Prints methods available decoupleR. first column correspond function name decoupleR second method's full name.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/show_methods.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show methods — show_methods","text":"","code":"show_methods()"},{"path":"https://saezlab.github.io/decoupleR/reference/show_methods.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show methods — show_methods","text":"","code":"show_methods() #> # A tibble: 12 × 2 #>    Function      Name                                                            #>    <chr>         <chr>                                                           #>  1 run_aucell    AUCell                                                          #>  2 run_consensus Consensus score between methods                                 #>  3 run_fgsea     Fast Gene Set Enrichment Analysis (FGSEA)                       #>  4 run_gsva      Gene Set Variation Analysis (GSVA)                              #>  5 run_mdt       Multivariate Decision Trees (MDT)                               #>  6 run_mlm       Multivariate Linear Model (MLM)                                 #>  7 run_ora       Over Representation Analysis (ORA)                              #>  8 run_udt       Univariate Decision Tree (UDT)                                  #>  9 run_ulm       Univariate Linear Model (ULM)                                   #> 10 run_viper     Virtual Inference of Protein-activity by Enriched Regulon anal… #> 11 run_wmean     Weighted Mean (WMEAN)                                           #> 12 run_wsum      Weighted Sum (WSUM)"},{"path":"https://saezlab.github.io/decoupleR/reference/show_resources.html","id":null,"dir":"Reference","previous_headings":"","what":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","title":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","text":"Shows available resources Omnipath. information visit official website Omnipath.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/show_resources.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","text":"","code":"show_resources()"},{"path":"https://saezlab.github.io/decoupleR/reference/show_resources.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","text":"","code":"decoupleR::show_resources() #>  [1] \"Adhesome\"             \"Almen2009\"            \"Baccin2019\"           #>  [4] \"CORUM_Funcat\"         \"CORUM_GO\"             \"CSPA\"                 #>  [7] \"CSPA_celltype\"        \"CancerDrugsDB\"        \"CancerGeneCensus\"     #> [10] \"CancerSEA\"            \"CellCall\"             \"CellCellInteractions\" #> [13] \"CellChatDB\"           \"CellChatDB_complex\"   \"CellPhoneDB\"          #> [16] \"CellPhoneDB_complex\"  \"CellTalkDB\"           \"CellTypist\"           #> [19] \"Cellinker\"            \"Cellinker_complex\"    \"ComPPI\"               #> [22] \"CytoSig\"              \"DGIdb\"                \"DisGeNet\"             #> [25] \"EMBRACE\"              \"Exocarta\"             \"GO_Intercell\"         #> [28] \"GPCRdb\"               \"Guide2Pharma\"         \"HGNC\"                 #> [31] \"HPA_secretome\"        \"HPA_subcellular\"      \"HPA_tissue\"           #> [34] \"HPMR\"                 \"HumanCellMap\"         \"ICELLNET\"             #> [37] \"ICELLNET_complex\"     \"IntOGen\"              \"Integrins\"            #> [40] \"InterPro\"             \"KEGG-PC\"              \"Kirouac2010\"          #> [43] \"LOCATE\"               \"LRdb\"                 \"Lambert2018\"          #> [46] \"MCAM\"                 \"MSigDB\"               \"Matrisome\"            #> [49] \"MatrixDB\"             \"Membranome\"           \"NetPath\"              #> [52] \"OPM\"                  \"PROGENy\"              \"PanglaoDB\"            #> [55] \"Phobius\"              \"Phosphatome\"          \"Ramilowski2015\"       #> [58] \"Ramilowski_location\"  \"SIGNOR\"               \"SignaLink_function\"   #> [61] \"SignaLink_pathway\"    \"Surfaceome\"           \"TCDB\"                 #> [64] \"TFcensus\"             \"TopDB\"                \"UniProt_family\"       #> [67] \"UniProt_keyword\"      \"UniProt_location\"     \"UniProt_tissue\"       #> [70] \"UniProt_topology\"     \"Vesiclepedia\"         \"Wang\"                 #> [73] \"Zhong2015\"            \"connectomeDB2020\"     \"iTALK\"                #> [76] \"kinase.com\"           \"scConnect\"            \"scConnect_complex\"    #> [79] \"talklr\""},{"path":"https://saezlab.github.io/decoupleR/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"rlang::sym() creates symbol string syms() creates list symbols character vector. enquo() enquos() delay execution one several function arguments. enquo() returns single quoted expression, like blueprint delayed computation. enquos() returns list quoted expressions. expr() quotes new expression locally. mostly useful build new expressions around arguments captured enquo() enquos(): expr(mean(!!enquo(arg), na.rm = TRUE)). rlang::as_name() transforms quoted variable name string. Supplying something else quoted variable name error. unlike rlang::as_label() also returns single string supports kind R object input, including quoted function calls vectors. purpose summarise object single label. label often suitable default name. know quoted expression contains (instance expressions captured enquo() variable name, call function, unquoted constant), use as_label(). know quoted simple variable name, like enforce , use as_name(). learn tidy eval use tools, visit https://tidyeval.tidyverse.org Metaprogramming section Advanced R.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/tidyeval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy eval helpers — tidyeval","text":"","code":"if (FALSE) {     help(\"nse-defuse\", package = \"rlang\") }"},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-3","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.3.x","text":"ulm mlm now faster consume memory. mat now transformed matrix automatically.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"new-features-2-3","dir":"Changelog","previous_headings":"","what":"New features","title":"decoupleR 2.3.x","text":"Added get_collectri wrapper easily access CollecTRI Gene Regulatory Network Network Omnipath. Added get_ksn_omnipath wrapper easily access Kinase-Substrate network Omnipath.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-2","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.2.x","text":"Changed example mat net toy examples. Changed test data toy data.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"bugfixes-2-2","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"decoupleR 2.2.x","text":"ora now selects correctly top bottom genes p-value estimation. wmean wsum now handle named matrices one sample.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-1","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.1.x","text":"likelihood param deprecated, now , weights (positive negative) go mor column network. Methods still run likelihood specified, however set 1. Added minsize argument methods, set 5 default. Sources containing less value targets input mat removed calculations. Changed default behavior decouple function. Now methods specified statistics argument, function run top performers benchmark (mlm, ulm wsum). run methods like , set statistics ‘’. Moreover, argument consensus_stats added filter statistics calculation consensus score. default uses mlm, ulm norm_wsum, statistics==‘’ methods returned running decouple. viper method: Now properly handles weights mor normalizing -1 +1. ulm/mlm/udt/mdt methods: Changed processed input network. model matrix contained intersection features mat network’s targets, now incorporates features coming mat ensuring robust prediction. Prediction values may change slightly older versions. Deprecated sparse argument. ora method: Now takes top 5% features default input instead 300 bottom features. Added seed randomly break ties consensus method: longer based RobustRankAggreg. Now consensus score mean activities obtained double tailed z-score transformation. Discarded filter_regulons function. Moved major dependencies Suggest reduce number dependencies needed. Updated README adding: Kinase inference example Graphical abstract Manuscript citation New vignette style Updated documentation methods.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"new-features-2-1","dir":"Changelog","previous_headings":"","what":"New features","title":"decoupleR 2.1.x","text":"Added wrappers easily query Omnipath, one largest data-bases collecting prior-knowledge resources. Added functions: show_resources: shows available resources inside Omnipath. get_resource: gets resource Omnipath. get_dorothea: gets DoRothEA gene regulatory network transcription factor (TF) activity estimation. Note: version slightly different one package dorothea since contains new edges TFs also weights interactions confidence levels. get_progeny: gets PROGENy model pathway activity estimation. Added show_methods function, shows many statistics currently available. Added check_corr function, shows correlated regulators network . can used check co-linearity mlm mdt. Added new error mlm co-variables co-linear (regulators correlated fit model).","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"bugfixes-2-1","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"decoupleR 2.1.x","text":"wmean wsum now return correct empirical p-values. ulm, mlm, mdt udt now accept matrices one column input. Results ulm mlm now correctly return un-grouped. Methods correctly run mat column names.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-0","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.0.x","text":"method’s names changed make easier identify: pscira now called Weighted Sum (wsum). mean now called Weighted Mean (wmean). scira now called Univariate Linear Model (ulm). column name tf output tibbles changed source. Updated documentation methods. Updated vignette README. decouple function now accepts order mismatch list methods list methods’s arguments. Moved benchmark branch separate repository package: https://github.com/saezlab/decoupleRBench","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"new-features-2-0","dir":"Changelog","previous_headings":"","what":"New features","title":"decoupleR 2.0.x","text":"New methods added: Fast Gene Set Enrichment Analysis (fgsea). AUCell. Univariate Decision Tree (udt). Multivariate Decision Tree (mdt). Multivariate Linear Model (mlm). New decoupleR manuscript repository: https://github.com/saezlab/decoupleR_manuscript New consensus score based RobustRankAggreg::aggregateRanks() added running decouple multiple methods. New statistic corr_wmean inside wmean. Methods based permutations statistical tests now return also p-value obtained score (fgsea, mlm, ora, ulm, viper, wmean wsum). New error added network edges duplicated. New error added input matrix contains NAs Infs.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"new-features-1-1","dir":"Changelog","previous_headings":"","what":"New features","title":"decoupleR 1.1.x","text":"new features allow tidy selection. Making easier evaluate different types data method. instance, can specify columns use strings, integer position, symbol expression.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"methods-1-1","dir":"Changelog","previous_headings":"New features","what":"Methods","title":"decoupleR 1.1.x","text":"New decouple() integrates various member functions decoupleR statistics centralized evaluation. New family decoupleR statists shared documentation made : New run_gsva() incorporate convinient wrapper GSVA::gsva(). New run_mean() calculates unnormalized regulatory activity normalized (.e. z-score) one based empirical distribution. New run_ora() fisher exact test calculate regulatory activity. New run_pscira() uses logic equivalent run_mean() difference accept column likelihood. New run_scira() calculates regulatory activity coefficient β1 adjusted linear model. New run_viper() incorporate convinient wrapper viper::viper().","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"converters-1-1","dir":"Changelog","previous_headings":"New features","what":"Converters","title":"decoupleR 1.1.x","text":"New convert_to_() return entry without modification. New convert_to_gsva() return list regulons suitable GSVA::gsva(). New convert_to_mean() return tibble four columns: tf, target, mor likelihood. New convert_to_ora() returns named list regulons; tf associated targets. New convert_to_pscira() returns tibble three columns: tf, target mor. New convert_to_scira() returns tibble three columns: tf, target mor. New convert_to_viper() return list regulons suitable viper::viper()","code":""}]
+[{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"Introduction","text":"decoupleR R package distributed part Bioconductor project. install package, start R enter: Alternatively, can instead install latest development version GitHub :","code":"install.packages(\"BiocManager\") BiocManager::install(\"decoupleR\") BiocManager::install(\"saezlab/decoupleR\")"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"usage","dir":"Articles","previous_headings":"","what":"Usage","title":"Introduction","text":"decoupleR (Badia--Mompel, Santiago, Braunger, Geiss, Dimitrov, Müller-Dott, Taus, Dugourd, Holland, Flores, Saez-Rodriguez, 2022) contains different statistical methods extract biological activities omics data using prior knowledge. : AUCell: (Aibar, Bravo Gonzalez-Blas, Moerman, Huynh-Thu, Imrichova, Hulselmans, Rambow, Marine, Geurts, Aerts, van den Oord, Kalender Atak, Wouters, Aerts, 2017) Fast GSEA: (Korotkevich, Sukhov, Sergushichev, 2019) GSVA: (H{ä}nzelmann, Castelo, Guinney, 2013) viper: (Alvarez, Shen, Giorgi, Lachmann, Ding, Ye, Califano, 2016) vignette showcase use toy data.","code":""},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"libraries","dir":"Articles","previous_headings":"Usage","what":"Libraries","title":"Introduction","text":"decoupleR can imported :","code":"library(decoupleR)  # Extra libraries library(dplyr) library(pheatmap)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"input-data","dir":"Articles","previous_headings":"Usage","what":"Input data","title":"Introduction","text":"decoupleR needs matrix (mat) molecular readouts (gene expression, logFC, p-values, etc.) network relates target features (genes, proteins, etc.) “source” biological entities (pathways, transcription factors, molecular processes, etc.). methods also require mode regulation (MoR) interaction, defined negative positive weights. get example data-set, run: example consists two small populations samples (S, cols) different gene expression patterns (G, rows):  can see genes seem expressed one group samples vice-versa. Ideally, like capture differences gene programs interpretable biological entities. example summarizing gene expression transcription factor activities. toy data also contains simple net consisting 3 transcription factors (Ts) specific regulation target genes (either positive negative). network can visualized like graph. Green edges positive regulation (activation), red edges negative regulation (inactivation):  According network, first population samples show high activity T1 T3, second one T2.","code":"data <- decoupleR::get_toy_data()  mat <- data$mat head(mat,5)[,1:5] #>           S01       S02       S03        S04      S05 #> G01 9.3709584 9.3888607 9.8951935  8.7844590 8.431446 #> G02 8.5646982 8.2787888 8.4304691  8.8509076 8.655648 #> G03 8.3631284 8.1333213 8.2572694 10.4142076 8.321925 #> G04 8.6328626 8.6359504 9.7631631  8.0361226 8.783839 #> G05 0.4042683 0.2842529 0.4600974  0.2059986 1.575728  network <- data$network network #> # A tibble: 10 × 3 #>    source target   mor #>    <chr>  <chr>  <dbl> #>  1 T1     G01      1   #>  2 T1     G02      1   #>  3 T1     G03      0.7 #>  4 T2     G06      1   #>  5 T2     G07      0.5 #>  6 T2     G08      1   #>  7 T3     G06     -0.5 #>  8 T3     G07     -3   #>  9 T3     G08     -1   #> 10 T3     G11      1 # Color scale colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  # Heatmap pheatmap::pheatmap(mat = mat,                    color = colors.use,                    border_color = \"white\",                    cluster_rows = FALSE,                    cluster_cols = FALSE,                    cellwidth = 15,                    cellheight = 15,                    treeheight_row = 0,                    treeheight_col = 0)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"methods","dir":"Articles","previous_headings":"Usage","what":"Methods","title":"Introduction","text":"decoupleR contains several methods. check many available, run: method models biological activities different manner, sometimes returning one estimate providing significance estimation. know method returns, please check documentation like ?run_mlm. unified framework, methods shared arguments: mat : input matrix molecular readouts. network : input prior knowledge information relating molecular features biological entities. .source refers biological entities. .target refers molecular features. .mor refers “strength” interaction (available, else 1s used). available methods can model interaction weights. minsize : Minimum target features per biological entity (5 default). less, sources removed. filtering prevents obtaining noisy activities biological entities matching target features matrix. example data-set keep 0 though.","code":"decoupleR::show_methods() #> # A tibble: 12 × 2 #>    Function      Name                                                            #>    <chr>         <chr>                                                           #>  1 run_aucell    AUCell                                                          #>  2 run_consensus Consensus score between methods                                 #>  3 run_fgsea     Fast Gene Set Enrichment Analysis (FGSEA)                       #>  4 run_gsva      Gene Set Variation Analysis (GSVA)                              #>  5 run_mdt       Multivariate Decision Trees (MDT)                               #>  6 run_mlm       Multivariate Linear Model (MLM)                                 #>  7 run_ora       Over Representation Analysis (ORA)                              #>  8 run_udt       Univariate Decision Tree (UDT)                                  #>  9 run_ulm       Univariate Linear Model (ULM)                                   #> 10 run_viper     Virtual Inference of Protein-activity by Enriched Regulon anal… #> 11 run_wmean     Weighted Mean (WMEAN)                                           #> 12 run_wsum      Weighted Sum (WSUM)"},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"individual-methods","dir":"Articles","previous_headings":"Usage > Running methods","what":"Individual methods","title":"Introduction","text":"example, let’s first run Gene Set Enrichment Analysis method (gsea), one well-known statistics: Methods return result data-frame containing: statistic: name statistic. Depending method, can one per method. source: name biological entity. condition: sample name. score: inferred biological activity. p_value: available, significance inferred activity. case gsea, returns simple estimate activities (fgsea), normalized estimate (norm_fgsea) p-values permutations. methods can return different things, example Univariate Linear Model (ulm): case, ulm returns just estimate (ulm) associated p-values. method can return different statistics, recommend check documentation know . Let us plot obtained results, first gsea:  can observe transcription factors T1 T2, obtained activities correctly distinguish two sample populations. T3, hand, second population samples since repressor. mislabeling activities happens gsea model weights inferring biological activities. weights available prior knowledge, definitely recommend using methods take account get better estimates, one example ulm:  Since ulm models weights estimating biological activities, correctly assigns T3 inactive second population samples.","code":"res_gsea <- decoupleR::run_fgsea(mat = mat,                                   network = network,                                   .source = 'source',                                   .target = 'target',                                   nproc = 1,                                   minsize = 0) #>   |                                                                              |                                                                      |   0%  |                                                                              |======================================================================| 100% 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|======================================================================| 100% #>  #>   |                                                                              |                                                                      |   0%  |                                                                              |===================================                                   |  50%  |                                                                              |======================================================================| 100%  res_gsea #> # A tibble: 144 × 5 #>    statistic  source condition   score p_value #>    <chr>      <chr>  <chr>       <dbl>   <dbl> #>  1 fgsea      T1     S01         0.889  0.0755 #>  2 norm_fgsea T1     S01         1.24   0.0755 #>  3 fgsea      T2     S01        -0.667  0.548  #>  4 norm_fgsea T2     S01        -1.11   0.548  #>  5 fgsea      T3     S01        -0.75   0.01   #>  6 norm_fgsea T3     S01       Inf      0.01   #>  7 fgsea      T1     S02         0.889  0.0764 #>  8 norm_fgsea T1     S02         1.29   0.0764 #>  9 fgsea      T2     S02         0      0.977  #> 10 norm_fgsea T2     S02         0      0.977  #> # ℹ 134 more rows res_ulm <- decoupleR::run_ulm(mat = mat,                                network = network,                                .source = 'source',                                .target = 'target',                                .mor = 'mor',                                minsize = 0)  res_ulm #> # A tibble: 72 × 5 #>    statistic source condition score  p_value #>    <chr>     <chr>  <chr>     <dbl>    <dbl> #>  1 ulm       T1     S01        4.21 0.00180  #>  2 ulm       T1     S02        4.07 0.00224  #>  3 ulm       T1     S03        3.85 0.00319  #>  4 ulm       T1     S04        4.60 0.000979 #>  5 ulm       T1     S05        3.90 0.00298  #>  6 ulm       T1     S06        3.66 0.00442  #>  7 ulm       T1     S07        4.31 0.00153  #>  8 ulm       T1     S08        4.65 0.000902 #>  9 ulm       T1     S09        4.49 0.00117  #> 10 ulm       T1     S10        4.07 0.00225  #> # ℹ 62 more rows # Transform to matrix mat_gsea <- res_gsea %>%             dplyr::filter(statistic == 'fgsea') %>%             decoupleR::pivot_wider_profile(id_cols = source,                                             names_from = condition,                                             values_from = score) %>%             as.matrix()  # Color scale colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  # Heatmap pheatmap::pheatmap(mat = mat_gsea,                    color = colors.use,                    border_color = \"white\",                    cluster_rows = FALSE,                    cluster_cols = FALSE,                    cellwidth = 20,                    cellheight = 20,                    treeheight_row = 0,                    treeheight_col = 0) # Transform to matrix mat_ulm <- res_ulm %>%            dplyr::filter(statistic=='ulm') %>%            decoupleR::pivot_wider_profile(id_cols = source,                                            names_from = condition,                                            values_from = score) %>%            as.matrix()  # Color scale colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  # Heatmap pheatmap::pheatmap(mat = mat_ulm,                    color = colors.use,                    border_color = \"white\",                    cluster_rows = FALSE,                    cluster_cols = FALSE,                    cellwidth = 20,                    cellheight = 20,                    treeheight_row = 0,                    treeheight_col = 0)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"multiple-methods","dir":"Articles","previous_headings":"Usage > Running methods","what":"Multiple methods","title":"Introduction","text":"decoupleR also allows run multiple methods time. Moreover, computes consensus score based obtained activities across methods, called consensus. default, deocuple runs top performer methods benchmark (mlm, ulm wsum), estimates consensus score across . Specific arguments specific methods can passed using variable args. information check ?decouple. Let us see result consensus score previous decouple run:  can observe consensus score correctly predicts T1 T3 active first population samples T2 second one.","code":"res_decouple <- decoupleR::decouple(mat,                                      network,                                      .source ='source',                                      .target ='target',                                     minsize = 0)  res_decouple #> # A tibble: 432 × 6 #>    run_id statistic source condition   score p_value #>     <dbl> <chr>     <chr>  <chr>       <dbl>   <dbl> #>  1      1 mlm       T1     S01        3.52   0.00781 #>  2      1 mlm       T2     S01       -1.13   0.290   #>  3      1 mlm       T3     S01       -0.247  0.811   #>  4      1 mlm       T1     S02        3.48   0.00831 #>  5      1 mlm       T2     S02       -0.213  0.837   #>  6      1 mlm       T3     S02       -0.353  0.733   #>  7      1 mlm       T1     S03        3.15   0.0135  #>  8      1 mlm       T2     S03       -0.638  0.541   #>  9      1 mlm       T3     S03        0.0749 0.942   #> 10      1 mlm       T1     S04        3.82   0.00512 #> # ℹ 422 more rows # Transform to matrix mat_consensus <- res_decouple %>%                  dplyr::filter(statistic == 'consensus') %>%                  decoupleR::pivot_wider_profile(id_cols = source,                                                  names_from = condition,                                                  values_from = score) %>%                  as.matrix() # Color scale colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  # Heatmap pheatmap::pheatmap(mat = mat_consensus,                    color = colors.use,                    border_color = \"white\",                    cluster_rows = FALSE,                    cluster_cols = FALSE,                    cellwidth = 20,                    cellheight = 20,                    treeheight_row = 0,                    treeheight_col = 0)"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Introduction","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R version 4.4.1 (2024-06-14) #>  os       Ubuntu 22.04.5 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-10-19 #>  pandoc   3.4 @ /usr/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package      * version date (UTC) lib source #>  backports      1.5.0   2024-05-23 [1] RSPM #>  bibtex         0.5.1   2023-01-26 [1] RSPM #>  BiocManager    1.30.25 2024-08-28 [1] RSPM #>  BiocParallel   1.38.0  2024-04-30 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0.6.5   2023-12-01 [1] RSPM #>  withr          3.0.1   2024-07-31 [1] RSPM #>  xfun           0.48    2024-10-03 [1] RSPM #>  xml2           1.3.6   2023-12-04 [1] RSPM #>  yaml           2.3.10  2024-07-26 [1] RSPM #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/decoupleR.html","id":"bibliography","dir":"Articles","previous_headings":"","what":"Bibliography","title":"Introduction","text":"[1] S. Aibar, C. Bravo Gonzalez-Blas, T. Moerman, et al. “SCENIC: Single-Cell Regulatory Network Inference Clustering”. : Nature Methods 14 (2017), pp. 1083-1086. DOI: 10.1038/nmeth.4463. [2] M. J. Alvarez, Y. Shen, F. M. Giorgi, et al. “Functional characterization somatic mutations cancer using network-based inference protein activity”. : Nature genetics 48.8 (2016), pp. 838–47. [3] P. Badia--Mompel, J. V. Santiago, J. Braunger, et al. “decoupleR: ensemble computational methods infer biological activities omics data”. : Bioinformatics Advances (2022). DOI: https://doi.org/10.1093/bioadv/vbac016. [4] S. Hänzelmann, R. Castelo, J. Guinney. “GSVA: gene set variation analysis microarray RNA-Seq data”. : BMC Bioinformatics 14 (2013), p. 7. DOI: 10.1186/1471-2105-14-7. URL: https://doi.org/10.1186/1471-2105-14-7. [5] G. Korotkevich, V. Sukhov, . Sergushichev. “Fast gene set enrichment analysis”. : bioRxiv (2019). DOI: 10.1101/060012. URL: http://biorxiv.org/content/early/2016/06/20/060012.","code":""},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Pathway activity inference in bulk RNA-seq","text":"First, need load relevant packages:","code":"## We load the required packages library(decoupleR) library(dplyr) library(tibble) library(tidyr) library(ggplot2) library(pheatmap) library(ggrepel)"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Pathway activity inference in bulk RNA-seq","text":"used already processed bulk RNA-seq data-set. provide normalized log-transformed counts, experimental design meta-data Differential Expressed Genes (DEGs) obtained using limma. example use limma used DeSeq2, edgeR statistical framework. decoupleR requires gene level statistic perform enrichment analysis agnostic generated. However, recommend use statistics include direction change significance, example t-value obtained limma(t) DeSeq2(stat). edgeR return statistic can create weighting obtained logFC pvalue formula: -log10(pvalue) * logFC. can open data like : data can extract mentioned information. see normalized log-transformed counts: design meta-data: results limma, interested extracting obtained t-value contrast:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"bk_data.rds\")) # Remove NAs and set row names counts <- data$counts %>%           dplyr::mutate_if(~ any(is.na(.x)),                             ~ dplyr::if_else(is.na(.x), 0, .x)) %>%            tibble::column_to_rownames(var = \"gene\") %>%            as.matrix()  head(counts) #>          PANC1.WT.Rep1 PANC1.WT.Rep2 PANC1.WT.Rep3 PANC1.FOXA2KO.Rep1 #> NOC2L        10.052588     11.949123     12.057774          12.312291 #> PLEKHN1       7.535115      8.125993      8.714880           8.048196 #> PERM1         6.281242      6.424582      6.589668           6.293285 #> ISG15        10.938252     11.469081     11.425415          11.549986 #> AGRN          6.956335      7.196108      7.522550           7.061549 #> C1orf159      9.546224      9.788721      9.794589           9.850830 #>          PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO.Rep3 #> NOC2L             12.139918          11.494205 #> PLEKHN1            8.290154           8.621239 #> PERM1              6.486136           6.775344 #> ISG15             11.371464          11.178157 #> AGRN               7.485534           7.071555 #> C1orf159           9.988069           9.965357 design <- data$design  design #> # A tibble: 6 × 2 #>   sample             condition     #>   <chr>              <chr>         #> 1 PANC1.WT.Rep1      PANC1.WT      #> 2 PANC1.WT.Rep2      PANC1.WT      #> 3 PANC1.WT.Rep3      PANC1.WT      #> 4 PANC1.FOXA2KO.Rep1 PANC1.FOXA2KO #> 5 PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO #> 6 PANC1.FOXA2KO.Rep3 PANC1.FOXA2KO # Extract t-values per gene deg <- data$limma_ttop %>%        dplyr::select(ID, t) %>%         dplyr::filter(!is.na(t)) %>%         tibble::column_to_rownames(var = \"ID\") %>%        as.matrix()  head(deg) #>                  t #> RHBDL2  -12.810588 #> PLEKHH2 -10.794453 #> HEG1     -9.788112 #> CLU      -9.761618 #> FHL1      8.950191 #> RBP4     -8.529074"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"progeny-model","dir":"Articles","previous_headings":"","what":"PROGENy model","title":"Pathway activity inference in bulk RNA-seq","text":"PROGENy comprehensive resource containing curated collection pathways target genes, weights interaction. example use human weights (organisms available) use top 500 responsive genes ranked p-value. brief description pathway: Androgen: involved growth development male reproductive organs. EGFR: regulates growth, survival, migration, apoptosis, proliferation, differentiation mammalian cells Estrogen: promotes growth development female reproductive organs. Hypoxia: promotes angiogenesis metabolic reprogramming O2 levels low. JAK-STAT: involved immunity, cell division, cell death, tumor formation. MAPK: integrates external signals promotes cell growth proliferation. NFkB: regulates immune response, cytokine production cell survival. p53: regulates cell cycle, apoptosis, DNA repair tumor suppression. PI3K: promotes growth proliferation. TGFb: involved development, homeostasis, repair tissues. TNFa: mediates haematopoiesis, immune surveillance, tumour regression protection infection. Trail: induces apoptosis. VEGF: mediates angiogenesis, vascular permeability, cell migration. WNT: regulates organ morphogenesis development tissue repair. access can use decoupleR:","code":"net <- decoupleR::get_progeny(organism = 'human',                                top = 500)  net #> # A tibble: 7,000 × 4 #>    source   target  weight  p_value #>    <chr>    <chr>    <dbl>    <dbl> #>  1 Androgen TMPRSS2  11.5  2.38e-47 #>  2 Androgen NKX3-1   10.6  2.21e-44 #>  3 Androgen MBOAT2   10.5  4.63e-44 #>  4 Androgen KLK2     10.2  1.94e-40 #>  5 Androgen SARG     11.4  2.79e-40 #>  6 Androgen SLC38A4   7.36 1.25e-39 #>  7 Androgen MTMR9     6.13 2.53e-38 #>  8 Androgen ZBTB16   10.6  1.57e-36 #>  9 Androgen KCNN2     9.47 7.71e-36 #> 10 Androgen OPRK1    -5.63 1.11e-35 #> # ℹ 6,990 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"activity-inference-with-multivariate-linear-model-mlm","dir":"Articles","previous_headings":"","what":"Activity inference with Multivariate Linear Model (MLM)","title":"Pathway activity inference in bulk RNA-seq","text":"infer pathway enrichment scores run Multivariate Linear Model (mlm) method. sample dataset (mat), fits linear model predicts observed gene expression based pathways’ Pathway-Gene interactions weights. fitted, obtained t-values slopes scores. positive, interpret pathway active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Run mlm sample_acts <- decoupleR::run_mlm(mat = counts,                                    net = net,                                    .source = 'source',                                    .target = 'target',                                   .mor = 'weight',                                    minsize = 5) sample_acts #> # A tibble: 84 × 5 #>    statistic source   condition       score  p_value #>    <chr>     <chr>    <chr>           <dbl>    <dbl> #>  1 mlm       Androgen PANC1.WT.Rep1 -0.692  0.489    #>  2 mlm       EGFR     PANC1.WT.Rep1 -0.0414 0.967    #>  3 mlm       Estrogen PANC1.WT.Rep1 -0.361  0.718    #>  4 mlm       Hypoxia  PANC1.WT.Rep1 -2.06   0.0393   #>  5 mlm       JAK-STAT PANC1.WT.Rep1 -0.166  0.868    #>  6 mlm       MAPK     PANC1.WT.Rep1 -0.509  0.611    #>  7 mlm       NFkB     PANC1.WT.Rep1 -2.84   0.00447  #>  8 mlm       PI3K     PANC1.WT.Rep1  3.53   0.000423 #>  9 mlm       TGFb     PANC1.WT.Rep1 -1.43   0.152    #> 10 mlm       TNFa     PANC1.WT.Rep1  2.06   0.0395   #> # ℹ 74 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Pathway activity inference in bulk RNA-seq","text":"obtained results observe obtained activities per sample heat-map:  can also infer pathway activities t-values DEGs KO WT: Let’s show changes activity KO WT:  pathway p53 Trail deactivated KO compared WT, MAPKK JAK-STAT seem activated. can visualize responsive genes pathway along t-values interpret results. example, let’s see genes belong MAPK pathway:  pathway seems active since majority target genes positive weights positive t-values (1st quadrant), majority ones negative weights negative t-values (3d quadrant).","code":"# Transform to wide matrix sample_acts_mat <- sample_acts %>%                    tidyr::pivot_wider(id_cols = 'condition',                                        names_from = 'source',                                       values_from = 'score') %>%                    tibble::column_to_rownames('condition') %>%                    as.matrix()  # Scale per feature sample_acts_mat <- scale(sample_acts_mat)  # Color scale colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  my_breaks <- c(seq(-2, 0, length.out = ceiling(100 / 2) + 1),                seq(0.05,2, length.out = floor(100 / 2)))  # Plot pheatmap::pheatmap(mat = sample_acts_mat,                    color = colors.use,                    border_color = \"white\",                    breaks = my_breaks,                    cellwidth = 20,                    cellheight = 20,                    treeheight_row = 20,                    treeheight_col = 20) # Run mlm contrast_acts <- decoupleR::run_mlm(mat  =deg,                                      net = net,                                      .source = 'source',                                      .target = 'target',                                     .mor = 'weight',                                      minsize = 5)  contrast_acts #> # A tibble: 14 × 5 #>    statistic source   condition  score  p_value #>    <chr>     <chr>    <chr>      <dbl>    <dbl> #>  1 mlm       Androgen t         -0.219 8.27e- 1 #>  2 mlm       EGFR     t         -0.439 6.61e- 1 #>  3 mlm       Estrogen t          3.95  7.70e- 5 #>  4 mlm       Hypoxia  t          0.171 8.64e- 1 #>  5 mlm       JAK-STAT t          5.91  3.47e- 9 #>  6 mlm       MAPK     t         13.0   4.32e-38 #>  7 mlm       NFkB     t          1.36  1.75e- 1 #>  8 mlm       PI3K     t          5.65  1.65e- 8 #>  9 mlm       TGFb     t         -0.656 5.12e- 1 #> 10 mlm       TNFa     t          1.93  5.36e- 2 #> 11 mlm       Trail    t         -2.03  4.26e- 2 #> 12 mlm       VEGF     t          2.82  4.80e- 3 #> 13 mlm       WNT      t         -1.49  1.35e- 1 #> 14 mlm       p53      t         -4.80  1.60e- 6 # Plot colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")[c(2, 10)])  p <- ggplot2::ggplot(data = contrast_acts,                       mapping = ggplot2::aes(x = stats::reorder(source, score),                                              y = score)) +       ggplot2::geom_bar(mapping = ggplot2::aes(fill = score),                        color = \"black\",                        stat = \"identity\") +      ggplot2::scale_fill_gradient2(low = colors[1],                                     mid = \"whitesmoke\",                                     high = colors[2],                                     midpoint = 0) +       ggplot2::theme_minimal() +      ggplot2::theme(axis.title = element_text(face = \"bold\", size = 12),               axis.text.x = ggplot2::element_text(angle = 45,                                                    hjust = 1,                                                    size = 10,                                                    face = \"bold\"),               axis.text.y = ggplot2::element_text(size = 10,                                                    face = \"bold\"),               panel.grid.major = element_blank(),                panel.grid.minor = element_blank()) +      ggplot2::xlab(\"Pathways\")  p pathway <- 'MAPK'  df <- net %>%       dplyr::filter(source == pathway) %>%       dplyr::arrange(target) %>%       dplyr::mutate(ID = target,                      color = \"3\") %>%       tibble::column_to_rownames('target')  inter <- sort(dplyr::intersect(rownames(deg), rownames(df)))  df <- df[inter, ]  df['t_value'] <- deg[inter, ]  df <- df %>%       dplyr::mutate(color = dplyr::if_else(weight > 0 & t_value > 0, '1', color)) %>%       dplyr::mutate(color = dplyr::if_else(weight > 0 & t_value < 0, '2', color)) %>%       dplyr::mutate(color = dplyr::if_else(weight < 0 & t_value > 0, '2', color)) %>%       dplyr::mutate(color = dplyr::if_else(weight < 0 & t_value < 0, '1', color))  colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")[c(2, 10)])  p <- ggplot2::ggplot(data = df,                       mapping = ggplot2::aes(x = weight,                                              y = t_value,                                              color = color)) +       ggplot2::geom_point(size = 2.5,                           color = \"black\") +       ggplot2::geom_point(size = 1.5) +      ggplot2::scale_colour_manual(values = c(colors[2], colors[1], \"grey\")) +      ggrepel::geom_label_repel(mapping = ggplot2::aes(label = ID)) +       ggplot2::theme_minimal() +      ggplot2::theme(legend.position = \"none\") +      ggplot2::geom_vline(xintercept = 0, linetype = 'dotted') +      ggplot2::geom_hline(yintercept = 0, linetype = 'dotted') +      ggplot2::ggtitle(pathway)  p #> Warning: ggrepel: 447 unlabeled data points (too many overlaps). Consider #> increasing max.overlaps"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_bk.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Pathway activity inference in bulk RNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R version 4.4.1 (2024-06-14) #>  os       Ubuntu 22.04.5 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-10-19 #>  pandoc   3.4 @ /usr/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package      * version date (UTC) lib source #>  backports      1.5.0   2024-05-23 [1] RSPM #>  BiocManager    1.30.25 2024-08-28 [1] RSPM #>  BiocParallel   1.38.0  2024-04-30 [1] 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[1] RSPM #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Pathway activity inference from scRNA-seq","text":"First, need load relevant packages, Seurat handle scRNA-seq data decoupleR use statistical methods.","code":"## We load the required packages library(Seurat) library(decoupleR)  # Only needed for data handling and plotting library(dplyr) library(tibble) library(tidyr) library(patchwork) library(ggplot2) library(pheatmap)"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Pathway activity inference from scRNA-seq","text":"used -sampled version data used Seurat vignette. can open data like : can observe different cell types:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"sc_data.rds\")) p <- Seurat::DimPlot(data,                       reduction = \"umap\",                       label = TRUE,                       pt.size = 0.5) +       Seurat::NoLegend() p"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"progeny-model","dir":"Articles","previous_headings":"Loading the data-set","what":"PROGENy model","title":"Pathway activity inference from scRNA-seq","text":"PROGENy comprehensive resource containing curated collection pathways target genes, weights interaction. example use human weights (organisms available) use top 500 responsive genes ranked p-value. brief description pathway: Androgen: involved growth development male reproductive organs. EGFR: regulates growth, survival, migration, apoptosis, proliferation, differentiation mammalian cells Estrogen: promotes growth development female reproductive organs. Hypoxia: promotes angiogenesis metabolic reprogramming O2 levels low. JAK-STAT: involved immunity, cell division, cell death, tumor formation. MAPK: integrates external signals promotes cell growth proliferation. NFkB: regulates immune response, cytokine production cell survival. p53: regulates cell cycle, apoptosis, DNA repair tumor suppression. PI3K: promotes growth proliferation. TGFb: involved development, homeostasis, repair tissues. TNFa: mediates haematopoiesis, immune surveillance, tumour regression protection infection. Trail: induces apoptosis. VEGF: mediates angiogenesis, vascular permeability, cell migration. WNT: regulates organ morphogenesis development tissue repair. access can use decoupleR:","code":"net <- decoupleR::get_progeny(organism = 'human', top = 500) net #> # A tibble: 7,000 × 4 #>    source   target  weight  p_value #>    <chr>    <chr>    <dbl>    <dbl> #>  1 Androgen TMPRSS2  11.5  2.38e-47 #>  2 Androgen NKX3-1   10.6  2.21e-44 #>  3 Androgen MBOAT2   10.5  4.63e-44 #>  4 Androgen KLK2     10.2  1.94e-40 #>  5 Androgen SARG     11.4  2.79e-40 #>  6 Androgen SLC38A4   7.36 1.25e-39 #>  7 Androgen MTMR9     6.13 2.53e-38 #>  8 Androgen ZBTB16   10.6  1.57e-36 #>  9 Androgen KCNN2     9.47 7.71e-36 #> 10 Androgen OPRK1    -5.63 1.11e-35 #> # ℹ 6,990 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"activity-inference-with-multivariate-linear-model-mlm","dir":"Articles","previous_headings":"","what":"Activity inference with Multivariate Linear Model (MLM)","title":"Pathway activity inference from scRNA-seq","text":"infer pathway enrichment scores run Multivariate Linear Model (mlm) method. sample dataset (mat), fits linear model predicts observed gene expression based pathways’ Pathway-Gene interactions weights. fitted, obtained t-values slopes scores. positive, interpret pathway active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Extract the normalized log-transformed counts mat <- as.matrix(data@assays$RNA@data)  # Run mlm acts <- decoupleR::run_mlm(mat = mat,                             net = net,                             .source = 'source',                             .target = 'target',                            .mor = 'weight',                             minsize = 5) acts #> # A tibble: 2,240 × 5 #>    statistic source   condition         score  p_value #>    <chr>     <chr>    <chr>             <dbl>    <dbl> #>  1 mlm       Androgen AAACATACAACCAC-1  0.559 0.576    #>  2 mlm       EGFR     AAACATACAACCAC-1  3.63  0.000290 #>  3 mlm       Estrogen AAACATACAACCAC-1 -0.886 0.375    #>  4 mlm       Hypoxia  AAACATACAACCAC-1  1.22  0.224    #>  5 mlm       JAK-STAT AAACATACAACCAC-1 -1.02  0.308    #>  6 mlm       MAPK     AAACATACAACCAC-1 -2.74  0.00619  #>  7 mlm       NFkB     AAACATACAACCAC-1 -0.230 0.818    #>  8 mlm       PI3K     AAACATACAACCAC-1 -1.09  0.276    #>  9 mlm       TGFb     AAACATACAACCAC-1  0.248 0.804    #> 10 mlm       TNFa     AAACATACAACCAC-1  2.22  0.0264   #> # ℹ 2,230 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Pathway activity inference from scRNA-seq","text":"obtained results, select ulm activities store object new assay called pathwaysmlm: new assay can used plot activities. visualize Trail pathway, associated apoptosis, seems B NK cells active.","code":"# Extract mlm and store it in pathwaysmlm in data data[['pathwaysmlm']] <- acts %>%                          tidyr::pivot_wider(id_cols = 'source',                                              names_from = 'condition',                                             values_from = 'score') %>%                          tibble::column_to_rownames(var = 'source') %>%                          Seurat::CreateAssayObject(.)  # Change assay Seurat::DefaultAssay(object = data) <- \"pathwaysmlm\"  # Scale the data data <- Seurat::ScaleData(data) data@assays$pathwaysmlm@data <- data@assays$pathwaysmlm@scale.data p1 <- Seurat::DimPlot(data,                        reduction = \"umap\",                        label = TRUE,                        pt.size = 0.5) +        Seurat::NoLegend() +        ggplot2::ggtitle('Cell types')  colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")[c(2, 10)])  p2 <- Seurat::FeaturePlot(data, features = c(\"Trail\")) +        ggplot2::scale_colour_gradient2(low = colors[1], mid = 'white', high = colors[2]) +       ggplot2::ggtitle('Trail activity')  p <- p1 | p2 p"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"exploration","dir":"Articles","previous_headings":"","what":"Exploration","title":"Pathway activity inference from scRNA-seq","text":"can also see mean activity per group across pathways:  specific example, can observe Trail active B NK cells.","code":"# Extract activities from object as a long dataframe df <- t(as.matrix(data@assays$pathwaysmlm@data)) %>%       as.data.frame() %>%       dplyr::mutate(cluster = Seurat::Idents(data)) %>%       tidyr::pivot_longer(cols = -cluster,                            names_to = \"source\",                            values_to = \"score\") %>%       dplyr::group_by(cluster, source) %>%       dplyr::summarise(mean = mean(score))  # Transform to wide matrix top_acts_mat <- df %>%                 tidyr::pivot_wider(id_cols = 'cluster',                                     names_from = 'source',                                    values_from = 'mean') %>%                 tibble::column_to_rownames(var = 'cluster') %>%                 as.matrix()  # Color scale colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  my_breaks <- c(seq(-1.25, 0, length.out = ceiling(100 / 2) + 1),                seq(0.05, 1.25, length.out = floor(100 / 2)))  # Plot pheatmap::pheatmap(mat = top_acts_mat,                    color = colors.use,                    border_color = \"white\",                    breaks = my_breaks,                    cellwidth = 20,                    cellheight = 20,                    treeheight_row = 20,                    treeheight_col = 20)"},{"path":"https://saezlab.github.io/decoupleR/articles/pw_sc.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Pathway activity inference from scRNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R version 4.4.1 (2024-06-14) #>  os       Ubuntu 22.04.5 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-10-19 #>  pandoc   3.4 @ /usr/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package          * version date (UTC) lib source #>  abind              1.4-8   2024-09-12 [1] RSPM #>  backports          1.5.0   2024-05-23 [1] RSPM #>  BiocManager        1.30.25 2024-08-28 [1] RSPM #>  BiocParallel       1.38.0  2024-04-30 [1] Bioconduc~ #>  BiocStyle        * 2.32.1  2024-06-16 [1] Bioconduc~ #>  bit                4.5.0   2024-09-20 [1] RSPM #>  bit64              4.5.2   2024-09-22 [1] RSPM #>  bookdown           0.41    2024-10-16 [1] RSPM #>  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[1] RSPM #>  spatstat.random    3.3-2   2024-09-18 [1] RSPM #>  spatstat.sparse    3.1-0   2024-06-21 [1] RSPM #>  spatstat.univar    3.0-1   2024-09-05 [1] RSPM #>  spatstat.utils     3.1-0   2024-08-17 [1] RSPM #>  stringi            1.8.4   2024-05-06 [1] RSPM #>  stringr            1.5.1   2023-11-14 [1] RSPM #>  survival           3.7-0   2024-06-05 [1] RSPM (R 4.4.0) #>  systemfonts        1.1.0   2024-05-15 [1] RSPM #>  tensor             1.5     2012-05-05 [1] RSPM #>  textshaping        0.4.0   2024-05-24 [1] RSPM #>  tibble           * 3.2.1   2023-03-20 [1] RSPM #>  tidyr            * 1.3.1   2024-01-24 [1] RSPM #>  tidyselect         1.2.1   2024-03-11 [1] RSPM #>  timechange         0.3.0   2024-01-18 [1] RSPM #>  tzdb               0.4.0   2023-05-12 [1] RSPM #>  utf8               1.2.4   2023-10-22 [1] RSPM #>  uwot               0.2.2   2024-04-21 [1] RSPM #>  vctrs              0.6.5   2023-12-01 [1] RSPM #>  viridisLite        0.4.2   2023-05-02 [1] RSPM #>  vroom              1.6.5   2023-12-05 [1] RSPM #>  withr              3.0.1   2024-07-31 [1] RSPM #>  xfun               0.48    2024-10-03 [1] RSPM #>  xml2               1.3.6   2023-12-04 [1] RSPM #>  xtable             1.8-4   2019-04-21 [1] RSPM #>  yaml               2.3.10  2024-07-26 [1] RSPM #>  zoo                1.8-12  2023-04-13 [1] RSPM #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Transcription factor activity inference in bulk RNA-seq","text":"First, need load relevant packages:","code":"## We load the required packages library(decoupleR) library(dplyr) library(tibble) library(tidyr) library(ggplot2) library(pheatmap) library(ggrepel)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Transcription factor activity inference in bulk RNA-seq","text":"used already processed bulk RNA-seq data-set. provide normalized log-transformed counts, experimental design meta-data Differential Expressed Genes (DEGs) obtained using limma. example use limma used DeSeq2, edgeR statistical framework. decoupleR requires gene level statistic perform enrichment analysis agnostic generated. However, recommend use statistics include direction change significance, example t-value obtained limma(t) DeSeq2(stat). edgeR return statistic can create weighting obtained logFC pvalue formula: -log10(pvalue) * logFC. can open data like : data can extract mentioned information. see normalized log-transformed counts: design meta-data: results limma, interested extracting obtained t-value p-value contrast:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"bk_data.rds\")) # Remove NAs and set row names counts <- data$counts %>%           dplyr::mutate_if(~ any(is.na(.x)),                             ~ dplyr::if_else(is.na(.x), 0, .x)) %>%            tibble::column_to_rownames(var = \"gene\") %>%            as.matrix()  head(counts) #>          PANC1.WT.Rep1 PANC1.WT.Rep2 PANC1.WT.Rep3 PANC1.FOXA2KO.Rep1 #> NOC2L        10.052588     11.949123     12.057774          12.312291 #> PLEKHN1       7.535115      8.125993      8.714880           8.048196 #> PERM1         6.281242      6.424582      6.589668           6.293285 #> ISG15        10.938252     11.469081     11.425415          11.549986 #> AGRN          6.956335      7.196108      7.522550           7.061549 #> C1orf159      9.546224      9.788721      9.794589           9.850830 #>          PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO.Rep3 #> NOC2L             12.139918          11.494205 #> PLEKHN1            8.290154           8.621239 #> PERM1              6.486136           6.775344 #> ISG15             11.371464          11.178157 #> AGRN               7.485534           7.071555 #> C1orf159           9.988069           9.965357 design <- data$design  design #> # A tibble: 6 × 2 #>   sample             condition     #>   <chr>              <chr>         #> 1 PANC1.WT.Rep1      PANC1.WT      #> 2 PANC1.WT.Rep2      PANC1.WT      #> 3 PANC1.WT.Rep3      PANC1.WT      #> 4 PANC1.FOXA2KO.Rep1 PANC1.FOXA2KO #> 5 PANC1.FOXA2KO.Rep2 PANC1.FOXA2KO #> 6 PANC1.FOXA2KO.Rep3 PANC1.FOXA2KO # Extract t-values per gene deg <- data$limma_ttop %>%        dplyr::select(ID, logFC, t, P.Value) %>%         dplyr::filter(!is.na(t)) %>%         tibble::column_to_rownames(var = \"ID\") %>%        as.matrix()  head(deg) #>             logFC          t      P.Value #> RHBDL2  -1.823940 -12.810588 3.030276e-06 #> PLEKHH2 -1.568830 -10.794453 9.932046e-06 #> HEG1    -1.725806  -9.788112 1.939734e-05 #> CLU     -1.786200  -9.761618 1.975813e-05 #> FHL1     2.087082   8.950191 3.552199e-05 #> RBP4    -1.728960  -8.529074 4.904579e-05"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"collectri-network","dir":"Articles","previous_headings":"","what":"CollecTRI network","title":"Transcription factor activity inference in bulk RNA-seq","text":"CollecTRI comprehensive resource containing curated collection TFs transcriptional targets compiled 12 different resources. collection provides increased coverage transcription factors superior performance identifying perturbed TFs compared previous DoRothEA network literature based GRNs. Similar DoRothEA, interactions weighted mode regulation (activation inhibition). example use human version (mouse rat also available). can use decoupleR retrieve OmniPath. argument split_complexes keeps complexes splits subunits, default recommend keep complexes together.","code":"net <- decoupleR::get_collectri(organism = 'human',                                  split_complexes = FALSE)  net #> # A tibble: 43,178 × 3 #>    source target   mor #>    <chr>  <chr>  <dbl> #>  1 MYC    TERT       1 #>  2 SPI1   BGLAP      1 #>  3 SMAD3  JUN        1 #>  4 SMAD4  JUN        1 #>  5 STAT5A IL2        1 #>  6 STAT5B IL2        1 #>  7 RELA   FAS        1 #>  8 WT1    NR0B1      1 #>  9 NR0B2  CASP1      1 #> 10 SP1    ALDOA      1 #> # ℹ 43,168 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"activity-inference-with-univariate-linear-model-ulm","dir":"Articles","previous_headings":"","what":"Activity inference with Univariate Linear Model (ULM)","title":"Transcription factor activity inference in bulk RNA-seq","text":"infer TF enrichment scores run Univariate Linear Model (ulm) method. sample dataset (mat) TF network (net), fits linear model predicts observed gene expression based solely TF’s TF-Gene interaction weights. fitted, obtained t-value slope score. positive, interpret TF active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Run ulm sample_acts <- decoupleR::run_ulm(mat = counts,                                    net = net,                                    .source = 'source',                                    .target = 'target',                                   .mor = 'mor',                                    minsize = 5)  sample_acts #> # A tibble: 3,480 × 5 #>    statistic source condition           score p_value #>    <chr>     <chr>  <chr>               <dbl>   <dbl> #>  1 ulm       ABL1   PANC1.FOXA2KO.Rep1 -0.428  0.669  #>  2 ulm       ABL1   PANC1.FOXA2KO.Rep2 -0.104  0.917  #>  3 ulm       ABL1   PANC1.FOXA2KO.Rep3  0.335  0.738  #>  4 ulm       ABL1   PANC1.WT.Rep1       0.142  0.887  #>  5 ulm       ABL1   PANC1.WT.Rep2      -0.344  0.731  #>  6 ulm       ABL1   PANC1.WT.Rep3      -0.523  0.601  #>  7 ulm       AHR    PANC1.FOXA2KO.Rep1  1.58   0.113  #>  8 ulm       AHR    PANC1.FOXA2KO.Rep2  1.70   0.0885 #>  9 ulm       AHR    PANC1.FOXA2KO.Rep3  1.85   0.0640 #> 10 ulm       AHR    PANC1.WT.Rep1       1.38   0.169  #> # ℹ 3,470 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Transcription factor activity inference in bulk RNA-seq","text":"obtained results observe variable activities across samples heat-map:  can also infer TF activities t-values DEGs KO WT: Let’s show changes activity KO WT:  TFs GLI3 SPDEF deactivated KO compared WT, MUC NFKB1 seem activated. can visualize differential target genes TF along p-values interpret results. example, let’s see genes belong SP1:  blue means sign multiplying mor t-value negative, meaning genes “deactivating” TF, red means sign positive, meaning genes “activating” TF.","code":"n_tfs <- 25  # Transform to wide matrix sample_acts_mat <- sample_acts %>%                    tidyr::pivot_wider(id_cols = 'condition',                                        names_from = 'source',                                       values_from = 'score') %>%                    tibble::column_to_rownames('condition') %>%                    as.matrix()  # Get top tfs with more variable means across clusters tfs <- sample_acts %>%        dplyr::group_by(source) %>%        dplyr::summarise(std = stats::sd(score)) %>%        dplyr::arrange(-abs(std)) %>%        head(n_tfs) %>%        dplyr::pull(source)  sample_acts_mat <- sample_acts_mat[,tfs]  # Scale per sample sample_acts_mat <- scale(sample_acts_mat)  # Choose color palette colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  my_breaks <- c(seq(-2, 0, length.out = ceiling(100 / 2) + 1),                seq(0.05, 2, length.out = floor(100 / 2)))  # Plot pheatmap::pheatmap(mat = sample_acts_mat,                    color = colors.use,                    border_color = \"white\",                    breaks = my_breaks,                    cellwidth = 15,                    cellheight = 15,                    treeheight_row = 20,                    treeheight_col = 20) # Run ulm contrast_acts <- decoupleR::run_ulm(mat = deg[, 't', drop = FALSE],                                      net = net,                                      .source = 'source',                                      .target = 'target',                                     .mor='mor',                                      minsize = 5)  contrast_acts #> # A tibble: 580 × 5 #>    statistic source condition   score p_value #>    <chr>     <chr>  <chr>       <dbl>   <dbl> #>  1 ulm       ABL1   t          1.08    0.280  #>  2 ulm       AHR    t          1.19    0.234  #>  3 ulm       AIRE   t         -0.155   0.877  #>  4 ulm       AP1    t          2.42    0.0154 #>  5 ulm       APEX1  t          0.877   0.380  #>  6 ulm       AR     t         -0.264   0.792  #>  7 ulm       ARID1A t         -0.236   0.813  #>  8 ulm       ARID3A t          1.85    0.0639 #>  9 ulm       ARID3B t          1.24    0.215  #> 10 ulm       ARID4A t         -0.0674  0.946  #> # ℹ 570 more rows # Filter top TFs in both signs f_contrast_acts <- contrast_acts %>%                    dplyr::mutate(rnk = NA)  msk <- f_contrast_acts$score > 0  f_contrast_acts[msk, 'rnk'] <- rank(-f_contrast_acts[msk, 'score']) f_contrast_acts[!msk, 'rnk'] <- rank(-abs(f_contrast_acts[!msk, 'score']))  tfs <- f_contrast_acts %>%        dplyr::arrange(rnk) %>%        head(n_tfs) %>%        dplyr::pull(source)  f_contrast_acts <- f_contrast_acts %>%                    filter(source %in% tfs)  colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")[c(2, 10)])  p <- ggplot2::ggplot(data = f_contrast_acts,                       mapping = ggplot2::aes(x = stats::reorder(source, score),                                              y = score)) +       ggplot2::geom_bar(mapping = ggplot2::aes(fill = score),                        color = \"black\",                        stat = \"identity\") +      ggplot2::scale_fill_gradient2(low = colors[1],                                     mid = \"whitesmoke\",                                     high = colors[2],                                     midpoint = 0) +       ggplot2::theme_minimal() +      ggplot2::theme(axis.title = element_text(face = \"bold\", size = 12),               axis.text.x = ggplot2::element_text(angle = 45,                                                    hjust = 1,                                                    size = 10,                                                    face = \"bold\"),               axis.text.y = ggplot2::element_text(size = 10,                                                    face = \"bold\"),               panel.grid.major = element_blank(),                panel.grid.minor = element_blank()) +      ggplot2::xlab(\"TFs\")  p tf <- 'SP1'  df <- net %>%       dplyr::filter(source == tf) %>%       dplyr::arrange(target) %>%       dplyr::mutate(ID = target, color = \"3\") %>%       tibble::column_to_rownames('target')  inter <- sort(dplyr::intersect(rownames(deg), rownames(df)))  df <- df[inter, ]  df[,c('logfc', 't_value', 'p_value')] <- deg[inter, ]  df <- df %>%       dplyr::mutate(color = dplyr::if_else(mor > 0 & t_value > 0, '1', color)) %>%       dplyr::mutate(color = dplyr::if_else(mor > 0 & t_value < 0, '2', color)) %>%       dplyr::mutate(color = dplyr::if_else(mor < 0 & t_value > 0, '2', color)) %>%       dplyr::mutate(color = dplyr::if_else(mor < 0 & t_value < 0, '1', color))  colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")[c(2, 10)])  p <- ggplot2::ggplot(data = df,                       mapping = ggplot2::aes(x = logfc,                                              y = -log10(p_value),                                              color = color,                                             size = abs(mor))) +       ggplot2::geom_point(size = 2.5,                           color = \"black\") +       ggplot2::geom_point(size = 1.5) +      ggplot2::scale_colour_manual(values = c(colors[2], colors[1], \"grey\")) +      ggrepel::geom_label_repel(mapping = ggplot2::aes(label = ID,                                                       size = 1)) +       ggplot2::theme_minimal() +      ggplot2::theme(legend.position = \"none\") +      ggplot2::geom_vline(xintercept = 0, linetype = 'dotted') +      ggplot2::geom_hline(yintercept = 0, linetype = 'dotted') +      ggplot2::ggtitle(tf)  p"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_bk.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Transcription factor activity inference in bulk RNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R version 4.4.1 (2024-06-14) #>  os       Ubuntu 22.04.5 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-10-19 #>  pandoc   3.4 @ /usr/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package      * version date (UTC) lib source #>  backports      1.5.0   2024-05-23 [1] RSPM #>  BiocManager    1.30.25 2024-08-28 [1] RSPM #>  BiocParallel   1.38.0  2024-04-30 [1] Bioconduc~ #>  BiocStyle 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fs             1.6.4   2024-04-25 [1] RSPM #>  generics       0.1.3   2022-07-05 [1] RSPM #>  ggplot2      * 3.5.1   2024-04-23 [1] RSPM #>  ggrepel      * 0.9.6   2024-09-07 [1] RSPM #>  glue           1.8.0   2024-09-30 [1] RSPM #>  gtable         0.3.5   2024-04-22 [1] RSPM #>  highr          0.11    2024-05-26 [1] RSPM #>  hms            1.1.3   2023-03-21 [1] RSPM #>  htmltools      0.5.8.1 2024-04-04 [1] RSPM #>  htmlwidgets    1.6.4   2023-12-06 [1] RSPM #>  httr           1.4.7   2023-08-15 [1] RSPM #>  igraph         2.0.3   2024-03-13 [1] RSPM #>  jquerylib      0.1.4   2021-04-26 [1] RSPM #>  jsonlite       1.8.9   2024-09-20 [1] RSPM #>  knitr          1.48    2024-07-07 [1] RSPM #>  labeling       0.4.3   2023-08-29 [1] RSPM #>  later          1.3.2   2023-12-06 [1] RSPM #>  lattice        0.22-6  2024-03-20 [2] CRAN (R 4.4.1) #>  lifecycle      1.0.4   2023-11-07 [1] RSPM #>  logger         0.3.0   2024-03-05 [1] RSPM #>  lubridate      1.9.3   2023-09-27 [1] RSPM #>  magrittr       2.0.3   2022-03-30 [1] RSPM #>  Matrix         1.7-1   2024-10-18 [1] RSPM (R 4.4.0) #>  munsell        0.5.1   2024-04-01 [1] RSPM #>  OmnipathR      3.12.4  2024-10-02 [1] Bioconduc~ #>  parallelly     1.38.0  2024-07-27 [1] RSPM #>  pheatmap     * 1.0.12  2019-01-04 [1] RSPM #>  pillar         1.9.0   2023-03-22 [1] RSPM #>  pkgconfig      2.0.3   2019-09-22 [1] RSPM #>  pkgdown        2.1.1   2024-09-17 [1] RSPM #>  prettyunits    1.2.0   2023-09-24 [1] RSPM #>  progress       1.2.3   2023-12-06 [1] RSPM #>  purrr          1.0.2   2023-08-10 [1] RSPM #>  R6             2.5.1   2021-08-19 [1] RSPM #>  ragg           1.3.3   2024-09-11 [1] RSPM #>  rappdirs       0.3.3   2021-01-31 [1] RSPM #>  RColorBrewer   1.1-3   2022-04-03 [1] RSPM #>  Rcpp           1.0.13  2024-07-17 [1] RSPM #>  readr          2.1.5   2024-01-10 [1] RSPM #>  readxl         1.4.3   2023-07-06 [1] RSPM #>  rlang          1.1.4   2024-06-04 [1] RSPM #>  rmarkdown      2.28    2024-08-17 [1] RSPM #>  rvest          1.0.4   2024-02-12 [1] RSPM #>  sass           0.4.9   2024-03-15 [1] RSPM #>  scales         1.3.0   2023-11-28 [1] RSPM #>  selectr        0.4-2   2019-11-20 [1] RSPM #>  sessioninfo    1.2.2   2021-12-06 [1] RSPM #>  stringi        1.8.4   2024-05-06 [1] RSPM #>  stringr        1.5.1   2023-11-14 [1] RSPM #>  systemfonts    1.1.0   2024-05-15 [1] RSPM #>  textshaping    0.4.0   2024-05-24 [1] RSPM #>  tibble       * 3.2.1   2023-03-20 [1] RSPM #>  tidyr        * 1.3.1   2024-01-24 [1] RSPM #>  tidyselect     1.2.1   2024-03-11 [1] RSPM #>  timechange     0.3.0   2024-01-18 [1] RSPM #>  tzdb           0.4.0   2023-05-12 [1] RSPM #>  utf8           1.2.4   2023-10-22 [1] RSPM #>  vctrs          0.6.5   2023-12-01 [1] RSPM #>  vroom          1.6.5   2023-12-05 [1] RSPM #>  withr          3.0.1   2024-07-31 [1] RSPM #>  xfun           0.48    2024-10-03 [1] RSPM #>  xml2           1.3.6   2023-12-04 [1] RSPM #>  yaml           2.3.10  2024-07-26 [1] RSPM #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"loading-packages","dir":"Articles","previous_headings":"","what":"Loading packages","title":"Transcription factor activity inference from scRNA-seq","text":"First, need load relevant packages, Seurat handle scRNA-seq data decoupleR use statistical methods.","code":"## We load the required packages library(Seurat) library(decoupleR)  # Only needed for data handling and plotting library(dplyr) library(tibble) library(tidyr) library(patchwork) library(ggplot2) library(pheatmap)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"loading-the-data-set","dir":"Articles","previous_headings":"","what":"Loading the data-set","title":"Transcription factor activity inference from scRNA-seq","text":"used -sampled version data used Seurat vignette. can open data like : can observe different cell types:","code":"inputs_dir <- system.file(\"extdata\", package = \"decoupleR\") data <- readRDS(file.path(inputs_dir, \"sc_data.rds\")) p <- Seurat::DimPlot(data,                       reduction = \"umap\",                       label = TRUE,                       pt.size = 0.5) +       Seurat::NoLegend()  p"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"collectri-network","dir":"Articles","previous_headings":"","what":"CollecTRI network","title":"Transcription factor activity inference from scRNA-seq","text":"CollecTRI comprehensive resource containing curated collection TFs transcriptional targets compiled 12 different resources. collection provides increased coverage transcription factors superior performance identifying perturbed TFs compared previous DoRothEA network literature based GRNs. Similar DoRothEA, interactions weighted mode regulation (activation inhibition). example use human version (mouse rat also available). can use decoupleR retrieve OmniPath. argument split_complexes keeps complexes splits subunits, default recommend keep complexes together.","code":"net <- decoupleR::get_collectri(organism = 'human',                                  split_complexes = FALSE)  net #> # A tibble: 43,178 × 3 #>    source target   mor #>    <chr>  <chr>  <dbl> #>  1 MYC    TERT       1 #>  2 SPI1   BGLAP      1 #>  3 SMAD3  JUN        1 #>  4 SMAD4  JUN        1 #>  5 STAT5A IL2        1 #>  6 STAT5B IL2        1 #>  7 RELA   FAS        1 #>  8 WT1    NR0B1      1 #>  9 NR0B2  CASP1      1 #> 10 SP1    ALDOA      1 #> # ℹ 43,168 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"activity-inference-with-univariate-linear-model-ulm","dir":"Articles","previous_headings":"","what":"Activity inference with Univariate Linear Model (ULM)","title":"Transcription factor activity inference from scRNA-seq","text":"infer TF enrichment scores run Univariate Linear Model (ulm) method. sample dataset (mat) TF network (net), fits linear model predicts observed gene expression based solely TF’s TF-Gene interaction weights. fitted, obtained t-value slope score. positive, interpret TF active negative interpret inactive. run decoupleR methods, need input matrix (mat), input prior knowledge network/resource (net), name columns net want use.","code":"# Extract the normalized log-transformed counts mat <- as.matrix(data@assays$RNA@data)  # Run ulm acts <- decoupleR::run_ulm(mat = mat,                             net = net,                             .source = 'source',                             .target = 'target',                            .mor='mor',                             minsize = 5)  acts #> # A tibble: 80,640 × 5 #>    statistic source condition         score p_value #>    <chr>     <chr>  <chr>             <dbl>   <dbl> #>  1 ulm       ABL1   AAACATACAACCAC-1  2.64  0.00820 #>  2 ulm       ABL1   AAACGCTGTTTCTG-1  0.893 0.372   #>  3 ulm       ABL1   AACCTTTGGACGGA-1  2.79  0.00525 #>  4 ulm       ABL1   AACGCCCTCGTACA-1  1.80  0.0721  #>  5 ulm       ABL1   AACGTCGAGTATCG-1  1.63  0.104   #>  6 ulm       ABL1   AACTCACTCAAGCT-1  1.71  0.0871  #>  7 ulm       ABL1   AAGATGGAAAACAG-1  1.12  0.264   #>  8 ulm       ABL1   AAGATTACCGCCTT-1  2.43  0.0151  #>  9 ulm       ABL1   AAGCCATGAACTGC-1  1.62  0.105   #> 10 ulm       ABL1   AAGGTCTGCAGATC-1 -0.292 0.771   #> # ℹ 80,630 more rows"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"visualization","dir":"Articles","previous_headings":"","what":"Visualization","title":"Transcription factor activity inference from scRNA-seq","text":"obtained results, store object new assay called tfsulm: new assay can used plot activities. observe activity inferred PAX5 across cells, particulary active B cells. Interestingly, PAX5 known TF crucial B cell identity function. inference activities “foot-prints” target genes informative just looking molecular readouts given TF, example gene expression PAX5, informative :","code":"# Extract ulm and store it in tfsulm in pbmc data[['tfsulm']] <- acts %>%                     tidyr::pivot_wider(id_cols = 'source',                                         names_from = 'condition',                                        values_from = 'score') %>%                     tibble::column_to_rownames('source') %>%                     Seurat::CreateAssayObject(.)  # Change assay DefaultAssay(object = data) <- \"tfsulm\"  # Scale the data data <- Seurat::ScaleData(data) data@assays$tfsulm@data <- data@assays$tfsulm@scale.data p1 <- Seurat::DimPlot(data,                        reduction = \"umap\",                        label = TRUE,                        pt.size = 0.5) +        Seurat::NoLegend() +        ggplot2::ggtitle('Cell types')   colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")[c(2, 10)])  p2 <- Seurat::FeaturePlot(data, features = c(\"PAX5\")) +        ggplot2::scale_colour_gradient2(low = colors[1], mid = 'white', high = colors[2]) +       ggplot2::ggtitle('PAX5 activity')   DefaultAssay(object = data) <- \"RNA\" p3 <- Seurat::FeaturePlot(data,                            features = c(\"PAX5\")) +        ggplot2::ggtitle('PAX5 expression')  Seurat::DefaultAssay(data) <- \"tfsulm\"  p <- p1 | p2 | p3 p"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"exploration","dir":"Articles","previous_headings":"","what":"Exploration","title":"Transcription factor activity inference from scRNA-seq","text":"can also see mean activity per group top 20 variable TFs:  can observe known marker TFs appearing, EBF1 B cells RFX5 myeloid lineage EOMES lymphoid.","code":"n_tfs <- 25  # Extract activities from object as a long dataframe df <- t(as.matrix(data@assays$tfsulm@data)) %>%       as.data.frame() %>%       dplyr::mutate(cluster = Seurat::Idents(data)) %>%       tidyr::pivot_longer(cols = -cluster,                            names_to = \"source\",                            values_to = \"score\") %>%       dplyr::group_by(cluster, source) %>%       dplyr::summarise(mean = mean(score))  # Get top tfs with more variable means across clusters tfs <- df %>%        dplyr::group_by(source) %>%        dplyr::summarise(std = stats::sd(mean)) %>%        dplyr::arrange(-abs(std)) %>%        head(n_tfs) %>%        dplyr::pull(source)  # Subset long data frame to top tfs and transform to wide matrix top_acts_mat <- df %>%                 dplyr::filter(source %in% tfs) %>%                 tidyr::pivot_wider(id_cols = 'cluster',                                     names_from = 'source',                                    values_from = 'mean') %>%                 tibble::column_to_rownames('cluster') %>%                 as.matrix()  # Choose color palette colors <- rev(RColorBrewer::brewer.pal(n = 11, name = \"RdBu\")) colors.use <- grDevices::colorRampPalette(colors = colors)(100)  my_breaks <- c(seq(-2, 0, length.out = ceiling(100 / 2) + 1),                seq(0.05, 2, length.out = floor(100 / 2)))  # Plot pheatmap::pheatmap(mat = top_acts_mat,                    color = colors.use,                    border_color = \"white\",                    breaks = my_breaks,                    cellwidth = 15,                    cellheight = 15,                    treeheight_row = 20,                    treeheight_col = 20)"},{"path":"https://saezlab.github.io/decoupleR/articles/tf_sc.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session information","title":"Transcription factor activity inference from scRNA-seq","text":"","code":"#> ─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────── #>  setting  value #>  version  R version 4.4.1 (2024-06-14) #>  os       Ubuntu 22.04.5 LTS #>  system   x86_64, linux-gnu #>  ui       X11 #>  language en #>  collate  en_US.UTF-8 #>  ctype    en_US.UTF-8 #>  tz       UTC #>  date     2024-10-19 #>  pandoc   3.4 @ /usr/bin/ (via rmarkdown) #>  #> ─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────── #>  package          * version date (UTC) lib source #>  abind              1.4-8   2024-09-12 [1] RSPM #>  backports          1.5.0   2024-05-23 [1] RSPM #>  BiocManager        1.30.25 2024-08-28 [1] RSPM #>  BiocParallel       1.38.0  2024-04-30 [1] Bioconduc~ #>  BiocStyle        * 2.32.1  2024-06-16 [1] Bioconduc~ #>  bit                4.5.0   2024-09-20 [1] RSPM #>  bit64              4.5.2   2024-09-22 [1] RSPM #>  bookdown           0.41    2024-10-16 [1] RSPM #>  bslib              0.8.0   2024-07-29 [1] RSPM #>  cachem             1.1.0   2024-05-16 [1] RSPM #>  cellranger         1.1.0   2016-07-27 [1] RSPM #>  checkmate          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1.3.6   2023-12-04 [1] RSPM #>  xtable             1.8-4   2019-04-21 [1] RSPM #>  yaml               2.3.10  2024-07-26 [1] RSPM #>  zoo                1.8-12  2023-04-13 [1] RSPM #>  #>  [1] /usr/local/lib/R/site-library #>  [2] /usr/local/lib/R/library #>  #> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────"},{"path":"https://saezlab.github.io/decoupleR/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Pau Badia--Mompel. Author, maintainer. Jesús Vélez-Santiago. Author. Jana Braunger. Author. Celina Geiss. Author. Daniel Dimitrov. Author. Sophia Müller-Dott. Author. Petr Taus. Author. Aurélien Dugourd. Author. Christian H. Holland. Author. Ricardo O. Ramirez Flores. Author. Julio Saez-Rodriguez. Author.","code":""},{"path":"https://saezlab.github.io/decoupleR/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Badia--Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov   D., Müller-Dott S., Taus P., Dugourd ., Holland C.H., Ramirez Flores R.O.   Saez-Rodriguez J. 2022. decoupleR: Ensemble computational methods   infer biological activities omics data. Bioinformatics Advances.   https://doi.org/10.1093/bioadv/vbac016","code":"@Article{,   author = {Pau Badia-i-Mompel and Jesús Vélez Santiago and Jana Braunger and Celina Geiss and Daniel Dimitrov and Sophia Müller-Dott and Petr Taus and Aurelien Dugourd and Christian H. Holland and Ricardo O. Ramirez Flores and Julio Saez-Rodriguez},   title = {decoupleR: ensemble of computational methods to infer biological activities from omics data},   journal = {Bioinformatics Advances},   year = {2022},   doi = {https://doi.org/10.1093/bioadv/vbac016}, }"},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"many methods allow us extract biological activities omics data. decoupleR Bioconductor package containing different statistical methods extract biological signatures prior knowledge within unified framework. Additionally, incorporates methods take account sign weight network interactions. decoupleR can used omic, long features can linked biological process based prior knowledge. example, transcriptomics gene sets regulated transcription factor, phospho-proteomics phosphosites targeted kinase. R version, faster memory efficient Python implementation go .  information package used real data, please check following links: decoupleR’s general usage Pathway activity inference bulk RNA-seq Pathway activity inference scRNA-seq Transcription factor activity inference bulk RNA-seq Transcription factor activity inference scRNA-seq Example Kinase TF activity estimation decoupleR’s manuscript repository Python implementation","code":""},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"decoupleR R package distributed part Bioconductor project. install package, start R enter: Alternatively, find error, try install latest version GitHub:","code":"install.packages('BiocManager') BiocManager::install('saezlab/decoupleR') install.packages('remotes') remotes::install_github('saezlab/decoupleR')"},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"Footprint methods inside decoupleR can used academic commercial purposes, except viper holds non-commercial license. data redistributed OmniPath license, original resource carries . one can find license information resources OmniPath.","code":""},{"path":"https://saezlab.github.io/decoupleR/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","text":"Badia--Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov D., Müller-Dott S., Taus P., Dugourd ., Holland C.H., Ramirez Flores R.O. Saez-Rodriguez J. 2022. decoupleR: ensemble computational methods infer biological activities omics data. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbac016","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":null,"dir":"Reference","previous_headings":"","what":"Check correlation (colinearity) — check_corr","title":"Check correlation (colinearity) — check_corr","text":"Checks correlation across regulators network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check correlation (colinearity) — check_corr","text":"","code":"check_corr(   network,   .source = \"source\",   .target = \"target\",   .mor = \"mor\",   .likelihood = NULL )"},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check correlation (colinearity) — check_corr","text":"network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check correlation (colinearity) — check_corr","text":"Correlation pairs tibble.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/check_corr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check correlation (colinearity) — check_corr","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") net <- readRDS(file.path(inputs_dir, \"net.rds\")) check_corr(net, .source='source') #> # A tibble: 3 × 3 #>   source source.2 correlation #>   <chr>  <chr>          <dbl> #> 1 T1     T3             0.364 #> 2 T2     T3            -0.487 #> 3 T1     T2            -0.688"},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":null,"dir":"Reference","previous_headings":"","what":"Rename columns and add defaults values if column not present — convert_f_defaults","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"convert_f_defaults() combine dplyr::rename() way working tibble::add_column() add columns default values case exist renaming data.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"","code":"convert_f_defaults(.data, ..., .def_col_val = c(), .use_dots = TRUE)"},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":".data data frame, data frame extension (e.g. tibble), lazy data frame (e.g. dbplyr dtplyr). See Methods, , details. ... rename(): <tidy-select> Use new_name = old_name rename selected variables. rename_with(): additional arguments passed onto .fn. .def_col_val Named vector columns default values none exist rename. .use_dots dot prefix added renamed variables? allow swapping columns.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"object type .data. output following properties: Rows affected. Column names changed. Column order function call.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"objective using .use_dots able swap columns , default, allowed dplyr::rename() function. behavior can replicated simply using dplyr::select(), however, select evaluation allows much flexibility unexpected results obtained. Despite , future implementation consider form execution allow renaming column multiple ones (.e. extend dataframe extension).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/convert_f_defaults.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rename columns and add defaults values if column not present — convert_f_defaults","text":"","code":"df <- tibble::tibble(x = 1, y = 2, z = 3)  # Rename columns df <- tibble::tibble(x = 1, y = 2) convert_f_defaults(     .data = df,     new_x = x,     new_y = y,     new_z = NULL,     .def_col_val = c(new_z = 3) ) #> # A tibble: 1 × 3 #>   new_x new_y new_z #>   <dbl> <dbl> <dbl> #> 1     1     2     3"},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate multiple statistics with same input data — decouple","title":"Evaluate multiple statistics with same input data — decouple","text":"Calculate source activity per sample gene expression matrix coupling regulatory network variety statistics.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate multiple statistics with same input data — decouple","text":"","code":"decouple(   mat,   network,   .source = source,   .target = target,   statistics = NULL,   args = list(NULL),   consensus_score = TRUE,   consensus_stats = NULL,   include_time = FALSE,   show_toy_call = FALSE,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate multiple statistics with same input data — decouple","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. statistics Statistical methods run sequentially. none provided, top performer methods run (mlm, ulm wsum). args list argument-lists length statistics (length 1). default argument, list(NULL), recycled length statistics, call function arguments (apart mat, network, .source , .target). consensus_score Boolean whether run consensus score methods. consensus_stats List estimate names use calculation consensus score. used filter extra estimations methods, example wsum returns wsum, corr_wsum norm_wsum. none provided, also statstics provided, top performer methods used (mlm, ulm norm_wsum). Else, use available estimates running methods statistics argument. include_time time per statistic evaluated informed? show_toy_call call statistic must informed? minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate multiple statistics with same input data — decouple","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: run_id: Indicates order methods executed. statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score). statistic_time: requested, internal execution time indicator. p_value: p-value (available) obtained score.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/decouple.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Evaluate multiple statistics with same input data — decouple","text":"","code":"if (FALSE) {     inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")      mat <- readRDS(file.path(inputs_dir, \"mat.rds\"))     net <- readRDS(file.path(inputs_dir, \"net.rds\"))      decouple(         mat = mat,         network = net,         .source = \"source\",         .target = \"target\",         statistics = c(\"gsva\", \"wmean\", \"wsum\", \"ulm\", \"aucell\"),         args = list(             gsva = list(verbose = FALSE),             wmean = list(.mor = \"mor\", .likelihood = \"likelihood\"),             wsum = list(.mor = \"mor\"),             ulm = list(.mor = \"mor\")         ),         minsize = 0     ) }"},{"path":"https://saezlab.github.io/decoupleR/reference/decoupleR-package.html","id":null,"dir":"Reference","previous_headings":"","what":"decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package","title":"decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package","text":"Many methods allow us extract biological activities omics data using information prior knowledge resources, reducing dimensionality increased statistical power better interpretability. , present decoupleR, Bioconductor package containing different statistical methods extract signatures within unified framework. decoupleR allows user flexibly test method resource. incorporates methods take account sign weight network interactions. decoupleR can used omic, long features can linked biological process based prior knowledge. example, transcriptomics gene sets regulated transcription factor, phospho-proteomics phosphosites targeted kinase.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/decoupleR-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data — decoupleR-package","text":"Maintainer: Pau Badia--Mompel pau.badia@uni-heidelberg.de (ORCID) Authors: Jesús Vélez-Santiago jvelezmagic@gmail.com (ORCID) Jana Braunger jana.bc@gmx.de (ORCID) Celina Geiss celina.geiss@stud.uni-heidelberg.de (ORCID) Daniel Dimitrov daniel.dimitrov@uni-heidelberg.de (ORCID) Sophia Müller-Dott sophia.mueller-dott@uni-heidelberg.de (ORCID) Petr Taus petr.taus@ceitec.muni.cz (ORCID) Aurélien Dugourd aurelien.dugourd@bioquant.uni-heidelberg.de (ORCID) Christian H. Holland cholland2408@gmail.com (ORCID) Ricardo O. Ramirez Flores roramirezf@uni-heidelberg.de  (ORCID) Julio Saez-Rodriguez pub.saez@uni-heidelberg.de (ORCID)","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_mat_format.html","id":null,"dir":"Reference","previous_headings":"","what":"DecoupleR mat format — .decoupler_mat_format","title":"DecoupleR mat format — .decoupler_mat_format","text":"DecoupleR mat format","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_mat_format.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DecoupleR mat format — .decoupler_mat_format","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html","id":null,"dir":"Reference","previous_headings":"","what":"DecoupleR network format — .decoupler_network_format","title":"DecoupleR network format — .decoupler_network_format","text":"network passed run_ method package must contain least two attributes: .source .target. addition, methods must map corresponding metadata associated edges.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DecoupleR network format — .decoupler_network_format","text":"network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-decoupler_network_format.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"DecoupleR network format — .decoupler_network_format","text":"attributes mapped prefixed . idea using type mapping provide flexibility different types networks, regulatory, metabolic, type. way, consider network networks long format can easily manipulated functions within tidyverse ecosystem.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":null,"dir":"Reference","previous_headings":"","what":"Pre-processing for methods that fit networks. — .fit_preprocessing","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"center true, expression values centered mean expression across samples.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"","code":".fit_preprocessing(network, mat, center, na.rm, sparse)"},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"network Tibble dataframe edges associated metadata. mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? sparse Deprecated parameter.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"named list matrices evaluate methods fit models, like .mlm_analysis(). mat: Features rows samples columns. mor_mat: Features rows columns source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/dot-fit_preprocessing.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pre-processing for methods that fit networks. — .fit_preprocessing","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) net <- rename_net(net, source, target, mor) .fit_preprocessing(net, mat, center = FALSE, na.rm = FALSE, sparse = FALSE) #> $mat #>            S01       S02       S03        S04        S05        S06        S07 #> G01 9.37095845 9.3888607 9.8951935  8.7844590 8.43144620 8.36723464 8.62351816 #> G02 8.56469817 8.2787888 8.4304691  8.8509076 8.65564788 8.18523056 8.95352336 #> G03 8.36312841 8.1333213 8.2572694 10.4142076 8.32192527 8.58182373 8.54282881 #> G04 8.63286260 8.6359504 9.7631631  8.0361226 8.78383894 9.39973683 8.58099650 #> G05 0.40426832 0.2842529 0.4600974  0.2059986 1.57572752 0.72729206 0.76817874 #> G06 0.10612452 2.6564554 0.6399949  0.3610573 0.64289931 1.30254263 0.46376759 #> G07 1.51152200 2.4404669 0.4554501  0.7581632 0.08976065 0.33584812 0.88577630 #> G08 0.09465904 1.3201133 0.7048373  0.7267048 0.27655075 1.03850610 1.09978090 #> G09 2.01842371 0.3066386 1.0351035  1.3682810 0.67928882 0.92072857 1.51270701 #> G10 0.06271410 1.7813084 0.6089264  0.4328180 0.08983289 0.72087816 0.25792144 #> G11 1.30486965 0.1719174 0.5049551  0.8113932 2.99309008 1.04311894 0.08844023 #> G12 2.28664539 1.2146747 1.7170087  1.4441013 0.28488295 0.09018639 0.12089654 #>           S08       S09       S10         S11        S12       S13         S14 #> G01 9.1943289 9.1317387 8.1881930 9.493625067 8.00006288 0.4138688 0.007762034 #> G02 8.6119969 9.4592140 8.1191610 9.470435741 9.12288964 1.1133860 0.800282178 #> G03 8.2171398 8.0799826 8.0250926 8.124702386 9.43985574 0.4809928 0.533492330 #> G04 8.1827567 8.6532043 8.1080727 8.996639135 9.09711377 0.4331690 1.287675246 #> G05 0.9333463 1.2009654 0.4854352 0.001822614 0.11731956 8.6968626 8.175525870 #> G06 0.8217731 1.0447511 0.5042171 0.428258881 1.20149840 9.0563684 9.071782384 #> G07 1.3921164 1.0032086 1.6610991 0.613671606 0.46972958 8.0406985 8.163206882 #> G08 0.4761739 1.8484819 0.3823337 2.024677845 0.05246948 9.5515448 8.362738416 #> G09 0.6503486 0.6667734 0.5126503 1.224747950 0.08610730 1.1671695 0.590013548 #> G10 1.3911105 0.1055138 2.7018910 0.179516441 0.88767902 0.2736457 1.432421928 #> G11 1.1107889 0.4222559 1.3621162 0.567620594 0.44468400 0.4678453 0.992692511 #> G12 0.8607926 0.1223502 0.1372562 0.492877354 0.02944488 1.2382523 0.454650298 #>             S15       S16       S17         S18       S19       S20         S21 #> G01 0.084898059 0.1514559 0.2526117  1.37686160 0.1320880 0.6585034  0.72921728 #> G02 0.895565582 0.5841090 1.2940025  1.15085557 1.4767874 1.2502366  0.99806891 #> G03 0.229778139 0.3688067 0.9591704  0.70582139 0.2170302 0.2717637  1.25848166 #> G04 0.836619068 0.2946543 1.0857749  1.05405578 1.2836022 0.9479520  1.24886369 #> G05 9.745055861 8.2792594 8.4037749  8.64574372 8.3856679 9.2015824  9.38063705 #> G06 9.689458921 9.3362367 8.5864875  8.18537797 8.3515129 8.4661161 10.04996069 #> G07 8.864777979 8.7007488 9.8152284  9.20122205 8.5217961 8.2693514  9.01687283 #> G08 8.150775989 8.5541966 8.1288214 10.03697217 9.0681312 8.3909654  8.02671746 #> G09 1.449007130 0.8363066 2.0009292  0.10777474 0.4283659 1.3487070  0.70360778 #> G10 0.643008700 1.5945882 0.3337772  0.08410810 0.1740182 0.0227647  0.97138523 #> G11 0.483193864 0.2049586 1.1713251  0.49561964 0.5156677 0.2442259  1.09615624 #> G12 0.006355626 0.3450880 2.0595392  0.03741519 0.2343653 0.9423717  0.04905045 #>           S22         S23        S24 #> G01 1.1984959  0.05399674 0.47039340 #> G02 0.1900190  1.06477321 1.24267027 #> G03 1.2977059  0.81319504 1.38157546 #> G04 1.0338737  0.19081647 1.20445894 #> G05 8.7384408 10.69992981 8.82407396 #> G06 8.0465639  8.06096664 9.66262940 #> G07 9.0175961  8.57375170 8.56930634 #> G08 8.3832840  8.04580358 8.63551382 #> G09 0.8727554  0.15741254 0.04372201 #> G10 0.9695450  0.43156537 0.34801230 #> G11 0.3838467  0.39654974 2.45959355 #> G12 1.8515557  1.30997823 0.81838032 #>  #> $mor_mat #>      T1  T2   T3 #> G01 1.0 0.0  0.0 #> G02 1.0 0.0  0.0 #> G03 0.7 0.0  0.0 #> G04 0.0 0.0  0.0 #> G05 0.0 0.0  0.0 #> G06 0.0 1.0 -0.5 #> G07 0.0 0.5 -3.0 #> G08 0.0 1.0 -1.0 #> G09 0.0 0.0  0.0 #> G10 0.0 0.0  0.0 #> G11 0.0 0.0  1.0 #> G12 0.0 0.0  0.0 #>"},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract sets — extract_sets","title":"Extract sets — extract_sets","text":"Extracts feature sets renamed network (see rename_net).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract sets — extract_sets","text":"","code":"extract_sets(network)"},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract sets — extract_sets","text":"network Tibble dataframe edges associated metadata.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/extract_sets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract sets — extract_sets","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) net <- rename_net(net, source, target, mor) extract_sets(net) #> $T1 #> [1] \"G01\" \"G02\" \"G03\" #>  #> $T2 #> [1] \"G06\" \"G07\" \"G08\" #>  #> $T3 #> [1] \"G06\" \"G07\" \"G08\" \"G11\" #>"},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter sources with minsize targets — filt_minsize","title":"Filter sources with minsize targets — filt_minsize","text":"Filter sources net less minsize targets","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter sources with minsize targets — filt_minsize","text":"","code":"filt_minsize(mat_f_names, network, minsize = 5)"},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter sources with minsize targets — filt_minsize","text":"mat_f_names Feature names mat. network Tibble dataframe edges associated metadata. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter sources with minsize targets — filt_minsize","text":"Filtered network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/filt_minsize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter sources with minsize targets — filt_minsize","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) net <- rename_net(net, source, target, mor) filt_minsize(rownames(mat), net, minsize = 4) #> # A tibble: 4 × 4 #>   source target   mor likelihood #>   <chr>  <chr>  <dbl>      <dbl> #> 1 T3     G06     -0.5          1 #> 2 T3     G07     -3            1 #> 3 T3     G08     -1            1 #> 4 T3     G11      1            1"},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":null,"dir":"Reference","previous_headings":"","what":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"CollecTRI gene regulatory network. Wrapper access CollecTRI gene regulatory network. CollecTRI comprehensive resource containing curated collection transcription factors (TFs) target genes. expansion DoRothEA. interaction weighted mode regulation (either positive negative).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"","code":"get_collectri(organism = \"human\", split_complexes = FALSE, ...)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"organism organism use. human, mouse rat available. split_complexes Whether split complexes subunits. default complexes kept . ... Ignored.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_collectri.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative). — get_collectri","text":"","code":"collectri <- get_collectri(organism='human', split_complexes=FALSE)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":null,"dir":"Reference","previous_headings":"","what":"DoRothEA gene regulatory network. — get_dorothea","title":"DoRothEA gene regulatory network. — get_dorothea","text":"Wrapper access DoRothEA gene regulatory network. DoRothEA comprehensive resource containing curated collection transcription factors (TFs) target genes. interaction weighted mode regulation (either positive negative) confidence level","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"DoRothEA gene regulatory network. — get_dorothea","text":"","code":"get_dorothea(   organism = \"human\",   levels = c(\"A\", \"B\", \"C\"),   weight_dict = list(A = 1, B = 2, C = 3, D = 4) )"},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DoRothEA gene regulatory network. — get_dorothea","text":"organism organism use. human, mouse rat available. levels List confidence levels return. Goes D, confident D less. weight_dict Dictionary values divide mode regulation (-1 1), one confidence level. Bigger values generate weights close zero.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_dorothea.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"DoRothEA gene regulatory network. — get_dorothea","text":"","code":"dorothea <- get_dorothea(organism='human', levels=c('A', 'B'))"},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":null,"dir":"Reference","previous_headings":"","what":"OmniPath kinase-substrate network — get_ksn_omnipath","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"Retrieve ready use, curated kinase-substrate Network OmniPath database.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"","code":"get_ksn_omnipath(...)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"... Passed OmnipathR::import_omnipath_enzsub.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_ksn_omnipath.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"OmniPath kinase-substrate network — get_ksn_omnipath","text":"Import enzyme-PTM network OmniPath, filter anything phospho dephosphorilation. format columns use decoupleR functions.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":null,"dir":"Reference","previous_headings":"","what":"Complete a data frame with missing combinations of data — get_profile_of","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"Turns implicit missing values explicit missing values. wrapper around expand(), dplyr::full_join() replace_na() useful completing missing combinations data.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"","code":"get_profile_of(data, sources, values_fill = NA)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"data data frame. sources named vector list values expand get profile. values_fill Optionally, (scalar) value specifies value filled missing. can named list want apply different fill values different value columns.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"data frame expanded grid values passed sources filled specified fill argument.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/get_profile_of.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Complete a data frame with missing combinations of data — get_profile_of","text":"","code":"if (FALSE) { # \\dontrun{ library(dplyr, warn.conflicts = FALSE) df <- tibble(     group = c(1:2, 1),     item_id = c(1:2, 2),     item_name = c(\"a\", \"b\", \"b\"),     value1 = 1:3,     value2 = 4:6 )  to_get_profile <- list(group = c(1, 2, 3), item_id = c(1, 2))  # This will add the combinations of group 3 with the id of the items df %>% get_profile_of(sources = to_get_profile)  # You can also choose to fill in missing values  # This only fill with \"Unknown\" the NA values of the column item_name df %>% get_profile_of(     sources = to_get_profile,     values_fill = list(item_name = \"Unknown\") )  # Replace all NAs with \"Unkwnon\" df %>% get_profile_of(sources = to_get_profile, values_fill = \"Unknown\") } # }"},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":null,"dir":"Reference","previous_headings":"","what":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"Wrapper access PROGENy model gene weights. pathway defined collection target genes, interaction associated p-value weight. top significant interactions per pathway returned.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"","code":"get_progeny(organism = \"human\", top = 500)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"organism organism use. human mouse available. top Number genes per pathway return.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_progeny.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pathway RespOnsive GENes for activity inference (PROGENy). — get_progeny","text":"","code":"progeny <- get_progeny(organism='human', top=500)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"Wrapper access resources inside Omnipath. wrapper allows easily query different prior knowledge resources. check available resources run decoupleR::show_resources(). information visit official website Omnipath.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"","code":"get_resource(name, organism = \"human\", ...)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"name Name resource query. organism Organism name NCBI Taxonomy ID. ... Passed OmnipathR::import_omnipath_annotations.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_resource.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run decoupleR::show_resources(). For more information visit the official website for Omnipath. — get_resource","text":"","code":"df <- decoupleR::get_resource('SIGNOR')"},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a toy mat and network. — get_toy_data","title":"Generate a toy mat and network. — get_toy_data","text":"Generate toy mat network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a toy mat and network. — get_toy_data","text":"","code":"get_toy_data(n_samples = 24, seed = 42)"},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a toy mat and network. — get_toy_data","text":"n_samples Number samples simulate. seed single value, interpreted integer, NULL random number generation.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a toy mat and network. — get_toy_data","text":"List containing mat network.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/get_toy_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a toy mat and network. — get_toy_data","text":"","code":"data <- get_toy_data() mat <- data$mat network <- data$network"},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":null,"dir":"Reference","previous_headings":"","what":"Intersect network target features with input matrix. — intersect_regulons","title":"Intersect network target features with input matrix. — intersect_regulons","text":"Keep edges target features belong input matrix.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Intersect network target features with input matrix. — intersect_regulons","text":"","code":"intersect_regulons(mat, network, .source, .target, minsize)"},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Intersect network target features with input matrix. — intersect_regulons","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. minsize Minimum number targets per source allowed.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Intersect network target features with input matrix. — intersect_regulons","text":"Filtered tibble.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/intersect_regulons.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Intersect network target features with input matrix. — intersect_regulons","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) intersect_regulons(mat, net, source, target, minsize=4) #> # A tibble: 4 × 3 #> # Groups:   source [1] #>   source target   mor #>   <chr>  <chr>  <dbl> #> 1 T3     G06     -0.5 #> 2 T3     G07     -3   #> 3 T3     G08     -1   #> 4 T3     G11      1"},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"Pipe object forward function call expression.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pipe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pipe operator — %>%","text":"","code":"c(1, 2, 3) %>% sum() #> [1] 6"},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":null,"dir":"Reference","previous_headings":"","what":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"Generates kind table rows come id_cols, columns names_from values values_from.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"","code":"pivot_wider_profile(   data,   id_cols,   names_from,   values_from,   values_fill = NA,   to_matrix = FALSE,   to_sparse = FALSE,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"data data frame pivot. id_cols <tidy-select> set columns uniquely identify observation. Typically used redundant variables, .e. variables whose values perfectly correlated existing variables. Defaults columns data except columns specified names_from values_from. tidyselect expression supplied, evaluated data removing columns specified names_from values_from. names_from, values_from <tidy-select> pair arguments describing column (columns) get name output column (names_from), column (columns) get cell values (values_from). values_from contains multiple values, value added front output column. values_fill Optionally, (scalar) value specifies value filled missing. can named list want apply different fill values different value columns. to_matrix Logical value indicating result matrix. Parameter ignored case sparse TRUE. to_sparse Logical value indicating whether resulting matrix sparse . ... Additional arguments passed methods.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"\"widened\" data; increasing number columns decreasing number rows.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"current state function, ensure operation, id_cols parameter single selector.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/pivot_wider_profile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pivot a data frame to wider and convert it to matrix — pivot_wider_profile","text":"","code":"if (FALSE) { # \\dontrun{ df <- tibble::tibble(     tf = c(\"tf_1\", \"tf_1\", \"tf_2\", \"tf_2\"),     gene = c(\"gene_1\", \"gene_2\", \"gene_1\", \"gene_2\"),     mor = c(1, -1, 1, -1) )  # Return a tibble pivot_wider_profile(     data = df,     id_cols = tf,     names_from = gene,     values_from = mor )  # Return a matrix pivot_wider_profile(     data = df,     id_cols = tf,     names_from = gene,     values_from = mor,     to_matrix = TRUE ) # Return a sparse Matrix of class \"dgCMatrix\" pivot_wider_profile(     data = df,     id_cols = tf,     names_from = gene,     values_from = mor,     to_sparse = TRUE ) } # }"},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Randomize matrix — randomize_matrix","title":"Randomize matrix — randomize_matrix","text":"Utility function used functions require permutations expression matrix","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Randomize matrix — randomize_matrix","text":"","code":"randomize_matrix(mat, randomize_type = c(\"rows\", \"cols_independently\"))"},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Randomize matrix — randomize_matrix","text":"mat Matrix randomize. randomize_type randomize.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Randomize matrix — randomize_matrix","text":"Randomized matrix","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/randomize_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Randomize matrix — randomize_matrix","text":"","code":"if (FALSE) { # \\dontrun{ mat <- matrix(seq_len(9), ncol = 3) mat  set.seed(42) randomize_matrix(mat, randomize_type = \"rows\")  set.seed(42) randomize_matrix(mat, randomize_type = \"cols_independently\") } # }"},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":null,"dir":"Reference","previous_headings":"","what":"Rename network — rename_net","title":"Rename network — rename_net","text":"Renames given network column names: .source, .target, .mor, .mor provided, function sets default values.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rename network — rename_net","text":"","code":"rename_net(   network,   .source,   .target,   .mor = NULL,   .likelihood = NULL,   def_mor = 1 )"},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rename network — rename_net","text":"network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. def_mor Default value .mor provided.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/rename_net.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rename network — rename_net","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\")) rename_net(net, source, target, mor) #> # A tibble: 10 × 4 #>    source target   mor likelihood #>    <chr>  <chr>  <dbl>      <dbl> #>  1 T1     G01      1            1 #>  2 T1     G02      1            1 #>  3 T1     G03      0.7          1 #>  4 T2     G06      1            1 #>  5 T2     G07      0.5          1 #>  6 T2     G08      1            1 #>  7 T3     G06     -0.5          1 #>  8 T3     G07     -3            1 #>  9 T3     G08     -1            1 #> 10 T3     G11      1            1"},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":null,"dir":"Reference","previous_headings":"","what":"AUCell — run_aucell","title":"AUCell — run_aucell","text":"Calculates regulatory activities using AUCell.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AUCell — run_aucell","text":"","code":"run_aucell(   mat,   network,   .source = source,   .target = target,   aucMaxRank = ceiling(0.05 * nrow(rankings)),   nproc = availableCores(),   seed = 42,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AUCell — run_aucell","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. aucMaxRank Threshold calculate AUC. nproc Number cores use computation. seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"AUCell — run_aucell","text":"AUCell (Aibar et al., 2017) uses Area Curve (AUC) calculate whether set targets enriched within molecular readouts sample. , AUCell first ranks molecular features sample highest lowest value, resolving ties randomly. , AUC can calculated using default top 5% molecular features ranking. Therefore, metric, aucell, represents proportion abundant molecular features target set, relative abundance value compared features within sample. Aibar S. et al. (2017) Scenic: single-cell regulatory network inference clustering. Nat. Methods, 14, 1083–1086.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_aucell.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"AUCell — run_aucell","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_aucell(mat, net, minsize=0, nproc=1, aucMaxRank=3) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 aucell    T1     S01       0.667 #>  2 aucell    T1     S02       0.667 #>  3 aucell    T1     S03       0.667 #>  4 aucell    T1     S04       1     #>  5 aucell    T1     S05       0.333 #>  6 aucell    T1     S06       0.333 #>  7 aucell    T1     S07       1     #>  8 aucell    T1     S08       1     #>  9 aucell    T1     S09       1     #> 10 aucell    T1     S10       1     #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":null,"dir":"Reference","previous_headings":"","what":"Consensus score between methods — run_consensus","title":"Consensus score between methods — run_consensus","text":"Function generate consensus score methods result decouple function.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Consensus score between methods — run_consensus","text":"","code":"run_consensus(df, include_time = FALSE, seed = NULL)"},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Consensus score between methods — run_consensus","text":"df decouple data frame result include_time time per statistic evaluated informed? seed Deprecated parameter.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Consensus score between methods — run_consensus","text":"Updated tibble computed consensus score methods","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_consensus.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Consensus score between methods — run_consensus","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\") mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  results <- decouple(    mat = mat,    network = net,    .source = \"source\",    .target = \"target\",    statistics = c(\"wmean\", \"ulm\"),    args = list(             wmean = list(.mor = \"mor\", .likelihood = \"likelihood\"),             ulm = list(.mor = \"mor\", .likelihood = \"likelihood\")         ),    consensus_score = FALSE,    minsize = 0    ) run_consensus(results) #> # A tibble: 72 × 6 #>    condition run_id statistic source  score p_value #>    <chr>      <dbl> <chr>     <chr>   <dbl>   <dbl> #>  1 S01            3 consensus T1      1.21    0.227 #>  2 S01            3 consensus T2     -0.327   0.744 #>  3 S01            3 consensus T3     -0.217   0.828 #>  4 S02            3 consensus T1      1.21    0.226 #>  5 S02            3 consensus T2     -0.267   0.789 #>  6 S02            3 consensus T3     -0.289   0.773 #>  7 S03            3 consensus T1      1.20    0.229 #>  8 S03            3 consensus T2     -0.320   0.749 #>  9 S03            3 consensus T3     -0.196   0.845 #> 10 S04            3 consensus T1      1.21    0.228 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":null,"dir":"Reference","previous_headings":"","what":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"Calculates regulatory activities using FGSEA.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"","code":"run_fgsea(   mat,   network,   .source = source,   .target = target,   times = 100,   nproc = availableCores(),   seed = 42,   minsize = 5,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. times many permutations ? nproc Number cores use computation. seed single value, interpreted integer, NULL. minsize Integer indicating minimum number targets per source. ... Arguments passed fgsea::fgseaMultilevel sampleSize size random set genes turn size = pathwaySize minSize Minimal size gene set test. pathways threshold excluded. maxSize Maximal size gene set test. pathways threshold excluded. eps parameter sets boundary calculating p value. scoreType parameter defines GSEA score type. Possible options (\"std\", \"pos\", \"neg\"). default (\"std\") enrichment score computed original GSEA. \"pos\" \"neg\" score types intended used one-tailed tests (.e. one interested positive (\"pos\") negateive (\"neg\") enrichment). gseaParam GSEA parameter value, gene-level statis raised power `gseaParam` calculation GSEA enrichment scores. BPPARAM Parallelization parameter used bplapply. Can used specify cluster run. initialized explicitly setting `nproc` default value `bpparam()` used. absEps deprecated, use `eps` parameter instead","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"GSEA (Aravind et al., 2005) starts transforming input molecular readouts mat ranks sample. , enrichment score fgsea calculated walking list features, increasing running-sum statistic feature target feature set encountered decreasing . final score maximum deviation zero encountered random walk. Finally, normalized score norm_fgsea, can obtained computing z-score estimate compared null distribution obtained N random permutations. used implementation taken package fgsea (Korotkevich et al., 2021). Aravind S. et al. (2005) Gene set enrichment analysis: knowledge-based approach interpreting genome-wide expression profiles. PNAS. 102, 43. Korotkevich G. et al. (2021) Fast gene set enrichment analysis. bioRxiv. DOI: https://doi.org/10.1101/060012.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_fgsea.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fast Gene Set Enrichment Analysis (FGSEA) — run_fgsea","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_fgsea(mat, net, minsize=0, nproc=1) #>    |                                                                               |                                                                      |   0%   |                                                                               |======================================================================| 100% #>  #>    |                                                                               |                                                                      | 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                                                       |===================================                                   |  50%   |                                                                               |======================================================================| 100% #>  #> # A tibble: 144 × 5 #>    statistic  source condition   score p_value #>    <chr>      <chr>  <chr>       <dbl>   <dbl> #>  1 fgsea      T1     S01         0.889  0.0755 #>  2 norm_fgsea T1     S01         1.24   0.0755 #>  3 fgsea      T2     S01        -0.667  0.548  #>  4 norm_fgsea T2     S01        -1.11   0.548  #>  5 fgsea      T3     S01        -0.75   0.01   #>  6 norm_fgsea T3     S01       Inf      0.01   #>  7 fgsea      T1     S02         0.889  0.0764 #>  8 norm_fgsea T1     S02         1.29   0.0764 #>  9 fgsea      T2     S02         0      0.977  #> 10 norm_fgsea T2     S02         0      0.977  #> # ℹ 134 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":null,"dir":"Reference","previous_headings":"","what":"Gene Set Variation Analysis (GSVA) — run_gsva","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"Calculates regulatory activities using GSVA.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"","code":"run_gsva(   mat,   network,   .source = source,   .target = target,   verbose = FALSE,   method = c(\"gsva\", \"plage\", \"ssgsea\", \"zscore\"),   minsize = 5L,   maxsize = Inf,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. verbose Gives information calculation step. Default: FALSE. method Method employ estimation gene-set enrichment. scores per sample. default set gsva (Hänzelmann et al, 2013). available methods \"plage\", \"ssgsea\" \"zscore\". Read manual GSVA::gsva. minsize Integer indicating minimum number targets per source. Must greater 0. maxsize Integer indicating maximum number targets per source. ... Arguments passed GSVA::gsvaParam, GSVA::ssgseaParam assay name assay use case exprData multi-assay container, otherwise ignored.  default, first assay used. annotation name Bioconductor annotation package gene identifiers occurring row names expression data matrix.  can used map gene identifiers occurring gene sets provided GeneSetCollection.  default gene identifiers used expression data matrix gene sets matched directly. kcdf Character vector length 1 denoting kernel use non-parametric estimation cumulative distribution function expression levels across samples.  default, kcdf=\"Gaussian\" suitable input expression values continuous, microarray fluorescent units logarithmic scale, RNA-seq log-CPMs, log-RPKMs log-TPMs.  input expression values integer counts, derived RNA-seq experiments, argument set kcdf=\"Poisson\". tau Numeric vector length 1.  exponent defining weight tail random walk performed GSVA (Hänzelmann et al., 2013) method.  default value 1 described paper. maxDiff Logical vector length 1 offers two approaches calculate enrichment statistic (ES) KS random walk statistic. FALSE: ES calculated maximum distance random walk 0. TRUE (default): ES calculated magnitude difference largest positive negative random walk deviations. absRanking Logical vector length 1 used maxDiff=TRUE. absRanking=FALSE (default) modified Kuiper statistic used calculate enrichment scores, taking magnitude difference largest positive negative random walk deviations. absRanking=TRUE original Kuiper statistic sums largest positive negative random walk deviations, used. latter case, gene sets genes enriched either extreme (high low) regarded ’highly’ activated. alpha Numeric vector length 1.  exponent defining weight tail random walk performed ssGSEA (Barbie et al., 2009) method.  default value 0.25 described paper. normalize Logical vector length 1; TRUE  runs ssGSEA method Barbie et al. (2009) normalizing scores absolute difference minimum maximum, described paper. Otherwise last normalization step skipped.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"GSVA (Hänzelmann et al., 2013) starts transforming input molecular readouts mat readout-level statistic using Gaussian kernel estimation cumulative density function. , readout-level statistics ranked per sample normalized -weight two tails rank distribution. Afterwards, enrichment score gsva calculated using running sum statistic normalized subtracting largest negative estimate largest positive one. Hänzelmann S. et al. (2013) GSVA: gene set variation analysis microarray RNA-seq data. BMC Bioinformatics, 14, 7.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_gsva.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Gene Set Variation Analysis (GSVA) — run_gsva","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_gsva(mat, net, minsize=1, verbose = FALSE) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 gsva      T1     S01       0.222 #>  2 gsva      T1     S02       0.556 #>  3 gsva      T1     S03       0.667 #>  4 gsva      T1     S04       0.778 #>  5 gsva      T1     S05       0.556 #>  6 gsva      T1     S06       0.667 #>  7 gsva      T1     S07       0.667 #>  8 gsva      T1     S08       0.667 #>  9 gsva      T1     S09       0.889 #> 10 gsva      T1     S10       0.444 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":null,"dir":"Reference","previous_headings":"","what":"Multivariate Decision Trees (MDT) — run_mdt","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"Calculates regulatory activities using MDT.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"","code":"run_mdt(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   trees = 10,   min_n = 20,   nproc = availableCores(),   seed = 42,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? trees integer number trees contained ensemble. min_n integer minimum number data points node required node split . nproc Number cores use computation. seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"MDT fits multivariate regression random forest sample, observed molecular readouts mat response variable regulator weights net covariates. Target features associated weight set zero. obtained feature importances fitted model activities mdt regulators net.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_mdt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Multivariate Decision Trees (MDT) — run_mdt","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_mdt(mat, net, minsize=0) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 mdt       T1     S01           0 #>  2 mdt       T1     S02           0 #>  3 mdt       T1     S03           0 #>  4 mdt       T1     S04           0 #>  5 mdt       T1     S05           0 #>  6 mdt       T1     S06           0 #>  7 mdt       T1     S07           0 #>  8 mdt       T1     S08           0 #>  9 mdt       T1     S09           0 #> 10 mdt       T1     S10           0 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":null,"dir":"Reference","previous_headings":"","what":"Multivariate Linear Model (MLM) — run_mlm","title":"Multivariate Linear Model (MLM) — run_mlm","text":"Calculates regulatory activities using MLM.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Multivariate Linear Model (MLM) — run_mlm","text":"","code":"run_mlm(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Multivariate Linear Model (MLM) — run_mlm","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Multivariate Linear Model (MLM) — run_mlm","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Multivariate Linear Model (MLM) — run_mlm","text":"MLM fits multivariate linear model sample, observed molecular readouts mat response variable regulator weights net covariates. Target features associated weight set zero. obtained t-values fitted model activities (mlm) regulators net.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_mlm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Multivariate Linear Model (MLM) — run_mlm","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_mlm(mat, net, minsize=0) #> # A tibble: 72 × 5 #>    statistic source condition   score p_value #>    <chr>     <chr>  <chr>       <dbl>   <dbl> #>  1 mlm       T1     S01        3.52   0.00781 #>  2 mlm       T2     S01       -1.13   0.290   #>  3 mlm       T3     S01       -0.247  0.811   #>  4 mlm       T1     S02        3.48   0.00831 #>  5 mlm       T2     S02       -0.213  0.837   #>  6 mlm       T3     S02       -0.353  0.733   #>  7 mlm       T1     S03        3.15   0.0135  #>  8 mlm       T2     S03       -0.638  0.541   #>  9 mlm       T3     S03        0.0749 0.942   #> 10 mlm       T1     S04        3.82   0.00512 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":null,"dir":"Reference","previous_headings":"","what":"Over Representation Analysis (ORA) — run_ora","title":"Over Representation Analysis (ORA) — run_ora","text":"Calculates regulatory activities using ORA.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Over Representation Analysis (ORA) — run_ora","text":"","code":"run_ora(   mat,   network,   .source = source,   .target = target,   n_up = ceiling(0.05 * nrow(mat)),   n_bottom = 0,   n_background = 20000,   with_ties = TRUE,   seed = 42,   minsize = 5,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Over Representation Analysis (ORA) — run_ora","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. n_up Integer indicating number top targets slice mat. n_bottom Integer indicating number bottom targets slice mat. n_background Integer indicating background size sliced targets. specified number background targets determined total number unique targets union mat network. with_ties ties kept together? default, TRUE, may return rows request. Use FALSE ignore ties, return first n rows. seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source. ... Arguments passed stats::fisher.test workspace integer specifying size workspace     used network algorithm.  units 4 bytes.  used     non-simulated p-values larger \\(2 \\times 2\\) tables.     Since R version 3.5.0, also increases internal stack size     allows larger problems solved, however sometimes needing     hours.  cases, simulate.p.values=TRUE may     reasonable. hybrid logical. used larger \\(2 \\times 2\\)     tables, cases indicates whether exact probabilities     (default) hybrid approximation thereof computed. hybridPars numeric vector length 3, default describing     “Cochran's conditions” validity chisquare     approximation, see ‘Details’. control list named components low level algorithm     control.  present one used \"mult\", positive     integer \\(\\ge 2\\) default 30 used larger     \\(2 \\times 2\\) tables.  says many times much     space allocated paths keys: see file     fexact.c sources package. hypothesized odds ratio.  used     \\(2 \\times 2\\) case. alternative indicates alternative hypothesis must     one \"two.sided\", \"greater\" \"less\".     can specify just initial letter.  used     \\(2 \\times 2\\) case. conf.int logical indicating confidence interval     odds ratio \\(2 \\times 2\\) table     computed (returned). conf.level confidence level returned confidence     interval.  used \\(2 \\times 2\\) case     conf.int = TRUE. simulate.p.value logical indicating whether compute     p-values Monte Carlo simulation, larger \\(2 \\times       2\\) tables. B integer specifying number replicates used     Monte Carlo test.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Over Representation Analysis (ORA) — run_ora","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Over Representation Analysis (ORA) — run_ora","text":"ORA measures overlap target feature set list altered molecular features mat. altered molecular features can selected top bottom molecular readout distribution, default top 5% positive values. , contingency table build one-tailed Fisher’s exact test computed determine regulator’s set features -represented selected features data. resulting score, ora, minus log10 obtained p-value.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_ora.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Over Representation Analysis (ORA) — run_ora","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_ora(mat, net, minsize=0) #> # A tibble: 72 × 5 #>    statistic source condition score  p_value #>    <chr>     <chr>  <chr>     <dbl>    <dbl> #>  1 ora       T1     S01        3.82 0.000150 #>  2 ora       T1     S02        3.82 0.000150 #>  3 ora       T1     S03        3.82 0.000150 #>  4 ora       T1     S04        3.82 0.000150 #>  5 ora       T1     S05        0    1        #>  6 ora       T1     S06        0    1        #>  7 ora       T1     S07        3.82 0.000150 #>  8 ora       T1     S08        3.82 0.000150 #>  9 ora       T1     S09        3.82 0.000150 #> 10 ora       T1     S10        3.82 0.000150 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":null,"dir":"Reference","previous_headings":"","what":"Univariate Decision Tree (UDT) — run_udt","title":"Univariate Decision Tree (UDT) — run_udt","text":"Calculates regulatory activities using UDT.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Univariate Decision Tree (UDT) — run_udt","text":"","code":"run_udt(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   min_n = 20,   seed = 42,   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Univariate Decision Tree (UDT) — run_udt","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? min_n integer minimum number data points node required node split . seed single value, interpreted integer, NULL random number generation. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Univariate Decision Tree (UDT) — run_udt","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Univariate Decision Tree (UDT) — run_udt","text":"UDT fits single regression decision tree sample regulator, observed molecular readouts mat response variable regulator weights net explanatory one. Target features associated weight set zero. obtained feature importance fitted model activity udt given regulator.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_udt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Univariate Decision Tree (UDT) — run_udt","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_udt(mat, net, minsize=0) #> # A tibble: 72 × 4 #>    statistic source condition score #>    <chr>     <chr>  <chr>     <dbl> #>  1 udt       T1     S01           0 #>  2 udt       T1     S02           0 #>  3 udt       T1     S03           0 #>  4 udt       T1     S04           0 #>  5 udt       T1     S05           0 #>  6 udt       T1     S06           0 #>  7 udt       T1     S07           0 #>  8 udt       T1     S08           0 #>  9 udt       T1     S09           0 #> 10 udt       T1     S10           0 #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":null,"dir":"Reference","previous_headings":"","what":"Univariate Linear Model (ULM) — run_ulm","title":"Univariate Linear Model (ULM) — run_ulm","text":"Calculates regulatory activities using ULM.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Univariate Linear Model (ULM) — run_ulm","text":"","code":"run_ulm(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   sparse = FALSE,   center = FALSE,   na.rm = FALSE,   minsize = 5L )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Univariate Linear Model (ULM) — run_ulm","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. sparse Deprecated parameter. center Logical value indicating mat must centered base::rowMeans(). na.rm missing values (including NaN) omitted calculations base::rowMeans()? minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Univariate Linear Model (ULM) — run_ulm","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Univariate Linear Model (ULM) — run_ulm","text":"ULM fits linear model sample regulator, observed molecular readouts mat response variable regulator weights net explanatory one. Target features associated weight set zero. obtained t-value fitted model activity ulm given regulator.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_ulm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Univariate Linear Model (ULM) — run_ulm","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_ulm(mat, net, minsize=0) #> # A tibble: 72 × 5 #>    statistic source condition score  p_value #>    <chr>     <chr>  <chr>     <dbl>    <dbl> #>  1 ulm       T1     S01        4.21 0.00180  #>  2 ulm       T1     S02        4.07 0.00224  #>  3 ulm       T1     S03        3.85 0.00319  #>  4 ulm       T1     S04        4.60 0.000979 #>  5 ulm       T1     S05        3.90 0.00298  #>  6 ulm       T1     S06        3.66 0.00442  #>  7 ulm       T1     S07        4.31 0.00153  #>  8 ulm       T1     S08        4.65 0.000902 #>  9 ulm       T1     S09        4.49 0.00117  #> 10 ulm       T1     S10        4.07 0.00225  #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":null,"dir":"Reference","previous_headings":"","what":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"Calculates regulatory activities using VIPER.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"","code":"run_viper(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   verbose = FALSE,   minsize = 5,   pleiotropy = TRUE,   eset.filter = FALSE,   ... )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. verbose Logical, whether progression messages printed terminal. minsize Integer indicating minimum number targets per source. pleiotropy Logical, whether correction pleiotropic regulation performed. eset.filter Logical, whether dataset limited genes represented interactome. ... Arguments passed viper::viper dnull Numeric matrix null model, usually generated nullTtest nes Logical, whether enrichment score reported normalized method Character string indicating method computing single samples signature, either scale, rank, mad, ttest none bootstraps Integer indicating number bootstraps iterations perform. scale method implemented bootstraps. adaptive.size Logical, whether weighting scores taken account computing regulon size pleiotropyArgs list 5 numbers pleotropy correction indicating: regulators p-value threshold, pleiotropic interaction p-value threshold, minimum number targets overlap pleiotropic regulators, penalty pleiotropic interactions method computing pleiotropy, either absolute adaptive cores Integer indicating number cores use (1 Windows-based systems)","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score).","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"VIPER (Alvarez et al., 2016) estimates biological activities performing three-tailed enrichment score calculation. information check supplementary information decoupler manuscript original publication. Alvarez M.J.et al. (2016) Functional characterization somatic mutations cancer using network-based inference protein activity. Nat. Genet., 48, 838–847.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_viper.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) — run_viper","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_viper(mat, net, minsize=0, verbose = FALSE) #> # A tibble: 72 × 5 #>    statistic source condition score p_value #>    <chr>     <chr>  <chr>     <dbl>   <dbl> #>  1 viper     T1     S01        1.45  0.147  #>  2 viper     T1     S02        1.45  0.147  #>  3 viper     T1     S03        1.45  0.147  #>  4 viper     T1     S04        1.84  0.0662 #>  5 viper     T1     S05        1.22  0.224  #>  6 viper     T1     S06        1.25  0.209  #>  7 viper     T1     S07        1.62  0.106  #>  8 viper     T1     S08        1.76  0.0783 #>  9 viper     T1     S09        1.62  0.106  #> 10 viper     T1     S10        1.62  0.106  #> # ℹ 62 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Weighted Mean (WMEAN) — run_wmean","title":"Weighted Mean (WMEAN) — run_wmean","text":"Calculates regulatory activities using WMEAN.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Weighted Mean (WMEAN) — run_wmean","text":"","code":"run_wmean(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   times = 100,   seed = 42,   sparse = TRUE,   randomize_type = \"rows\",   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Weighted Mean (WMEAN) — run_wmean","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. times many permutations ? seed single value, interpreted integer, NULL random number generation. sparse matrices used calculation sparse? randomize_type randomize expression matrix. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Weighted Mean (WMEAN) — run_wmean","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score). p_value: p-value score method.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Weighted Mean (WMEAN) — run_wmean","text":"WMEAN infers regulator activities first multiplying target feature associated weight summed enrichment score wmean. Furthermore, permutations random target features can performed obtain null distribution can used compute z-score norm_wmean, corrected estimate corr_wmean multiplying wmean minus log10 obtained empirical p-value.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_wmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Weighted Mean (WMEAN) — run_wmean","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_wmean(mat, net, minsize=0) #> # A tibble: 216 × 5 #>    statistic  source condition score p_value #>    <chr>      <chr>  <chr>     <dbl>   <dbl> #>  1 corr_wmean T1     S01        15.0    0.02 #>  2 corr_wmean T1     S02        14.7    0.02 #>  3 corr_wmean T1     S03        15.2    0.02 #>  4 corr_wmean T1     S04        15.7    0.02 #>  5 corr_wmean T1     S05        14.4    0.02 #>  6 corr_wmean T1     S06        14.2    0.02 #>  7 corr_wmean T1     S07        14.8    0.02 #>  8 corr_wmean T1     S08        14.8    0.02 #>  9 corr_wmean T1     S09        15.3    0.02 #> 10 corr_wmean T1     S10        13.8    0.02 #> # ℹ 206 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":null,"dir":"Reference","previous_headings":"","what":"Weighted Sum (WSUM) — run_wsum","title":"Weighted Sum (WSUM) — run_wsum","text":"Calculates regulatory activities using WSUM.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Weighted Sum (WSUM) — run_wsum","text":"","code":"run_wsum(   mat,   network,   .source = source,   .target = target,   .mor = mor,   .likelihood = likelihood,   times = 100,   seed = 42,   sparse = TRUE,   randomize_type = \"rows\",   minsize = 5 )"},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Weighted Sum (WSUM) — run_wsum","text":"mat Matrix evaluate (e.g. expression matrix). Target nodes rows conditions columns. rownames(mat) must least one intersection elements network .target column. network Tibble dataframe edges associated metadata. .source Column source nodes. .target Column target nodes. .mor Column edge mode regulation (.e. mor). .likelihood Deprecated argument. Now always set 1. times many permutations ? seed single value, interpreted integer, NULL random number generation. sparse matrices used calculation sparse? randomize_type randomize expression matrix. minsize Integer indicating minimum number targets per source.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Weighted Sum (WSUM) — run_wsum","text":"long format tibble enrichment scores source across samples. Resulting tibble contains following columns: statistic: Indicates method associated score. source: Source nodes network. condition: Condition representing column mat. score: Regulatory activity (enrichment score). p_value: p-value score method.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Weighted Sum (WSUM) — run_wsum","text":"WSUM infers regulator activities first multiplying target feature associated weight summed enrichment score wsum. Furthermore, permutations random target features can performed obtain null distribution can used compute z-score norm_wsum, corrected estimate corr_wsum multiplying wsum minus log10 obtained empirical p-value.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/reference/run_wsum.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Weighted Sum (WSUM) — run_wsum","text":"","code":"inputs_dir <- system.file(\"testdata\", \"inputs\", package = \"decoupleR\")  mat <- readRDS(file.path(inputs_dir, \"mat.rds\")) net <- readRDS(file.path(inputs_dir, \"net.rds\"))  run_wsum(mat, net, minsize=0) #> # A tibble: 216 × 5 #>    statistic source condition score p_value #>    <chr>     <chr>  <chr>     <dbl>   <dbl> #>  1 corr_wsum T1     S01        40.4    0.02 #>  2 corr_wsum T1     S02        39.7    0.02 #>  3 corr_wsum T1     S03        41.0    0.02 #>  4 corr_wsum T1     S04        42.3    0.02 #>  5 corr_wsum T1     S05        38.9    0.02 #>  6 corr_wsum T1     S06        38.3    0.02 #>  7 corr_wsum T1     S07        40.0    0.02 #>  8 corr_wsum T1     S08        40.0    0.02 #>  9 corr_wsum T1     S09        41.2    0.02 #> 10 corr_wsum T1     S10        37.2    0.02 #> # ℹ 206 more rows"},{"path":"https://saezlab.github.io/decoupleR/reference/show_methods.html","id":null,"dir":"Reference","previous_headings":"","what":"Show methods — show_methods","title":"Show methods — show_methods","text":"Prints methods available decoupleR. first column correspond function name decoupleR second method's full name.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/show_methods.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Show methods — show_methods","text":"","code":"show_methods()"},{"path":"https://saezlab.github.io/decoupleR/reference/show_methods.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Show methods — show_methods","text":"","code":"show_methods() #> # A tibble: 12 × 2 #>    Function      Name                                                            #>    <chr>         <chr>                                                           #>  1 run_aucell    AUCell                                                          #>  2 run_consensus Consensus score between methods                                 #>  3 run_fgsea     Fast Gene Set Enrichment Analysis (FGSEA)                       #>  4 run_gsva      Gene Set Variation Analysis (GSVA)                              #>  5 run_mdt       Multivariate Decision Trees (MDT)                               #>  6 run_mlm       Multivariate Linear Model (MLM)                                 #>  7 run_ora       Over Representation Analysis (ORA)                              #>  8 run_udt       Univariate Decision Tree (UDT)                                  #>  9 run_ulm       Univariate Linear Model (ULM)                                   #> 10 run_viper     Virtual Inference of Protein-activity by Enriched Regulon anal… #> 11 run_wmean     Weighted Mean (WMEAN)                                           #> 12 run_wsum      Weighted Sum (WSUM)"},{"path":"https://saezlab.github.io/decoupleR/reference/show_resources.html","id":null,"dir":"Reference","previous_headings":"","what":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","title":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","text":"Shows available resources Omnipath. information visit official website Omnipath.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/show_resources.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","text":"","code":"show_resources()"},{"path":"https://saezlab.github.io/decoupleR/reference/show_resources.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shows available resources in Omnipath. For more information visit the official website for Omnipath. — show_resources","text":"","code":"decoupleR::show_resources() #>  [1] \"Adhesome\"             \"Almen2009\"            \"Baccin2019\"           #>  [4] \"CORUM_Funcat\"         \"CORUM_GO\"             \"CSPA\"                 #>  [7] \"CSPA_celltype\"        \"CancerDrugsDB\"        \"CancerGeneCensus\"     #> [10] \"CancerSEA\"            \"CellCall\"             \"CellCellInteractions\" #> [13] \"CellChatDB\"           \"CellChatDB_complex\"   \"CellPhoneDB\"          #> [16] \"CellPhoneDB_complex\"  \"CellTalkDB\"           \"CellTypist\"           #> [19] \"Cellinker\"            \"Cellinker_complex\"    \"ComPPI\"               #> [22] \"CytoSig\"              \"DGIdb\"                \"DisGeNet\"             #> [25] \"EMBRACE\"              \"Exocarta\"             \"GO_Intercell\"         #> [28] \"GPCRdb\"               \"Guide2Pharma\"         \"HGNC\"                 #> [31] \"HPA_secretome\"        \"HPA_subcellular\"      \"HPA_tissue\"           #> [34] \"HPMR\"                 \"HumanCellMap\"         \"ICELLNET\"             #> [37] \"ICELLNET_complex\"     \"IntOGen\"              \"Integrins\"            #> [40] \"InterPro\"             \"KEGG-PC\"              \"Kirouac2010\"          #> [43] \"LOCATE\"               \"LRdb\"                 \"Lambert2018\"          #> [46] \"MCAM\"                 \"MSigDB\"               \"Matrisome\"            #> [49] \"MatrixDB\"             \"Membranome\"           \"NetPath\"              #> [52] \"OPM\"                  \"PROGENy\"              \"PanglaoDB\"            #> [55] \"Phobius\"              \"Phosphatome\"          \"Ramilowski2015\"       #> [58] \"Ramilowski_location\"  \"SIGNOR\"               \"SignaLink_function\"   #> [61] \"SignaLink_pathway\"    \"Surfaceome\"           \"TCDB\"                 #> [64] \"TFcensus\"             \"TopDB\"                \"UniProt_family\"       #> [67] \"UniProt_keyword\"      \"UniProt_location\"     \"UniProt_tissue\"       #> [70] \"UniProt_topology\"     \"Vesiclepedia\"         \"Wang\"                 #> [73] \"Zhong2015\"            \"connectomeDB2020\"     \"iTALK\"                #> [76] \"kinase.com\"           \"scConnect\"            \"scConnect_complex\"    #> [79] \"talklr\""},{"path":"https://saezlab.github.io/decoupleR/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"rlang::sym() creates symbol string syms() creates list symbols character vector. enquo() enquos() delay execution one several function arguments. enquo() returns single quoted expression, like blueprint delayed computation. enquos() returns list quoted expressions. expr() quotes new expression locally. mostly useful build new expressions around arguments captured enquo() enquos(): expr(mean(!!enquo(arg), na.rm = TRUE)). rlang::as_name() transforms quoted variable name string. Supplying something else quoted variable name error. unlike rlang::as_label() also returns single string supports kind R object input, including quoted function calls vectors. purpose summarise object single label. label often suitable default name. know quoted expression contains (instance expressions captured enquo() variable name, call function, unquoted constant), use as_label(). know quoted simple variable name, like enforce , use as_name(). learn tidy eval use tools, visit https://tidyeval.tidyverse.org Metaprogramming section Advanced R.","code":""},{"path":"https://saezlab.github.io/decoupleR/reference/tidyeval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy eval helpers — tidyeval","text":"","code":"if (FALSE) {     help(\"nse-defuse\", package = \"rlang\") }"},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-3","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.3.x","text":"ulm mlm now faster consume memory. mat now transformed matrix automatically.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"new-features-2-3","dir":"Changelog","previous_headings":"","what":"New features","title":"decoupleR 2.3.x","text":"Added get_collectri wrapper easily access CollecTRI Gene Regulatory Network Network Omnipath. Added get_ksn_omnipath wrapper easily access Kinase-Substrate network Omnipath.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-2","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.2.x","text":"Changed example mat net toy examples. Changed test data toy data.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"bugfixes-2-2","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"decoupleR 2.2.x","text":"ora now selects correctly top bottom genes p-value estimation. wmean wsum now handle named matrices one sample.","code":""},{"path":[]},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"changes-2-1","dir":"Changelog","previous_headings":"","what":"Changes","title":"decoupleR 2.1.x","text":"likelihood param deprecated, now , weights (positive negative) go mor column network. Methods still run likelihood specified, however set 1. Added minsize argument methods, set 5 default. Sources containing less value targets input mat removed calculations. Changed default behavior decouple function. Now methods specified statistics argument, function run top performers benchmark (mlm, ulm wsum). run methods like , set statistics ‘’. Moreover, argument consensus_stats added filter statistics calculation consensus score. default uses mlm, ulm norm_wsum, statistics==‘’ methods returned running decouple. viper method: Now properly handles weights mor normalizing -1 +1. ulm/mlm/udt/mdt methods: Changed processed input network. model matrix contained intersection features mat network’s targets, now incorporates features coming mat ensuring robust prediction. Prediction values may change slightly older versions. Deprecated sparse argument. ora method: Now takes top 5% features default input instead 300 bottom features. Added seed randomly break ties consensus method: longer based RobustRankAggreg. Now consensus score mean activities obtained double tailed z-score transformation. Discarded filter_regulons function. Moved major dependencies Suggest reduce number dependencies needed. Updated README adding: Kinase inference example Graphical abstract Manuscript citation New vignette style Updated documentation methods.","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"new-features-2-1","dir":"Changelog","previous_headings":"","what":"New features","title":"decoupleR 2.1.x","text":"Added wrappers easily query Omnipath, one largest data-bases collecting prior-knowledge resources. Added functions: show_resources: shows available resources inside Omnipath. get_resource: gets resource Omnipath. get_dorothea: gets DoRothEA gene regulatory network transcription factor (TF) activity estimation. Note: version slightly different one package dorothea since contains new edges TFs also weights interactions confidence levels. get_progeny: gets PROGENy model pathway activity estimation. Added show_methods function, shows many statistics currently available. Added check_corr function, shows correlated regulators network . can used check co-linearity mlm mdt. Added new error mlm co-variables co-linear (regulators correlated fit model).","code":""},{"path":"https://saezlab.github.io/decoupleR/news/index.html","id":"bugfixes-2-1","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"decoupleR 2.1.x","text":"wmean wsum now return correct empirical p-values. ulm, mlm, mdt udt now accept matrices one column input. Results ulm mlm now correctly return un-grouped. 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