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phylogenetics2.tex
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phylogenetics2.tex
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\documentclass[]{standalone}
%\usepackage[x11names, rgb]{xcolor}
%\usepackage[utf8]{inputenc}
\def\pgfsysdriver{pgfsys-tex4ht.def}
\usepackage{tikz}
\usetikzlibrary{snakes,arrows,shapes}
\usepackage{amsmath}
\usepackage[colorlinks=true,urlcolor=blue]{hyperref}
\def\pgfsysdriver{pgfsys-tex4ht.def}
\begin{document}
\tikzset{every text node part/.style={align=center}}%
\tikzstyle{model}=[draw=yellow!50, very thick, rectangle,fill=yellow!20]%
\tikzstyle{objective}=[draw=gray!50, very thick, rectangle,fill=gray!20]%
\tikzstyle{data}=[draw=red!50, very thick, fill=red!20]%
\tikzstyle{algo}=[draw=blue!50, very thick, fill=blue!20,ellipse]%
\tikzstyle{treestyle}=[draw=green!50, very thick, fill=green!20]%
\begin{tikzpicture}[>=latex',line join=bevel]
\node (distances) at (8,8) [data] {Genetic\\distance\\matrix\\($\hat d$: $n \times n$)};
\node (ml_objective) at (18,8) [objective] {Maximum\\likelihood\\objective};
\node (sequences) at (8,21) [data] {DNA\\sequences};
\node (nj_algorithm) at (6,4) [algo] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lecture5/#/23}{Neighbour-joining}\\algorithm\\$O(n^3)$};
\node (nj_tree) at (6,0) [treestyle] {Neighbour-joining\\tree\\(unrooted)};
\node (felsenstein_pruning) at (16,12) [algo] {Felsenstein's\\\href{http://alexeidrummond.org/bayesian_phylo_lectures/lectureSubstitutionModels/#/7}{pruning algorithm}\\$\Pr(D|T,Q)$};
\node (sequence_alignment) at (8,18.5) [algo] {MSA\\algorithm};
\node (ls) at (2.5,0) [treestyle] {Least-squares\\tree};
\node (ls_objective) at (2.5,4) [objective] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lecture5/#/28}{Least-squares}\\objective};
\node (bayesian_inference) at (14,8) [algo] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lecture9/#/}{Bayesian MCMC}\\algorithm\\$f(T,Q,\theta|D)$};
\node (bayesian_posterior) at (14,4) [treestyle] {Posterior\\distribution\\on trees};
\node (matrix_exponentiation) at (16,16) [algo] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lectureSubstitutionModels/#/2/10}{Matrix exponential}\\$P(d)=\exp(Qd)$};
\node (treeprior) at (12,12) [model] {Model-based\\tree prior\\$f(T|\theta)$};
\node (substmodel) at (12,18.5) [model] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lectureSubstitutionModels/#/2/7}{CTMC}\\Substitution model\\($Q$)};
\node (maximum_parsimony) at (0,4) [treestyle] {Maximum\\parsimony\\tree\\(unrooted)};
\node (maximum_likelihood) at (18,4) [treestyle] {Maximum\\likelihood\\tree};
\node (msa) at (8,16) [data] {Multiple\\sequence\\alignment\\($D$: $n \times L$)};
\node (parsimony_objective) at (0,8) [objective] {Maximum\\parsimony\\objective};
\node (parsimony_algorithm) at (3,12) [algo] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lecture6/#/13}{parsimony algorithm}\\$O(nL)$};
\node (distance_correction) at (8,12) [algo] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lectureSubstitutionModels/#/2/16}{distance correction}\\$\hat d_{ij}=f_{corr}(p_{ij})$};
\node (upgma_algorithm) at (10.5,4) [algo] {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lecture5/#/19}{UPGMA}\\algorithm\\$O(n^2)$ or $O(n^3)$};
\node (upgma_tree) at (10.5,0) [treestyle] {UPGMA\\tree\\(rooted, ultrametric)};
\draw [-stealth'] (matrix_exponentiation) -- node {Transition\\probabilities,\\$P(d)$} (felsenstein_pruning);
\draw [-stealth'] (distances) -- (nj_algorithm);
\draw [-stealth'] (substmodel) -- (matrix_exponentiation);
\draw [-stealth'] (msa) -- node {\href{http://alexeidrummond.org/bayesian_phylo_lectures/lectureSubstitutionModels/}{p-distances}\\($p$: $n \times n$)} (distance_correction);
\draw [-stealth'] (upgma_algorithm) -- (upgma_tree);
\draw [-stealth'] (msa) -- (parsimony_algorithm);
\draw [-stealth'] (nj_algorithm) -- (nj_tree);
\draw [-stealth'] (distances) -- (ls_objective);
\draw [-stealth'] (parsimony_objective) -- node {heuristic\\tree\\search} (maximum_parsimony);
\draw [-stealth'] (parsimony_algorithm) -- (parsimony_objective);
\draw [-stealth'] (ml_objective) -- node {heuristic\\tree\\search} (maximum_likelihood);
\draw [-stealth'] (felsenstein_pruning) -- (bayesian_inference);
\draw [-stealth'] (msa) -- (felsenstein_pruning);
\draw [-stealth'] (bayesian_inference) -- (bayesian_posterior);
\draw [-stealth'] (sequence_alignment) -- (msa);
\draw [-stealth'] (sequences) -- (sequence_alignment);
\draw [-stealth'] (treeprior) -- (bayesian_inference);
\draw [-stealth'] (distances) -- (upgma_algorithm);
\draw [-stealth'] (ls_objective) -- node {heuristic\\tree\\search} (ls);
\draw [-stealth'] (substmodel) -- (distance_correction);
\draw [-stealth'] (felsenstein_pruning) -- (ml_objective);
\draw [-stealth'] (distance_correction) -- (distances);
%
\end{tikzpicture}
% End of code
%
\end{document}
%