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DESCRIPTION
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DESCRIPTION
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Package: satuRn
Type: Package
Title: Scalable Analysis of Differential Transcript Usage for Bulk and Single-Cell RNA-sequencing Applications
Date: 2023-02-28
Version: 1.7.3
Authors@R: c(person("Jeroen", "Gilis", role = c("aut","cre"),
email = "[email protected]"),
person("Kristoffer", "Vitting-Seerup", role = "ctb",
email = "[email protected]"),
person("Koen","Van den Berge", role = "ctb",
email = "[email protected]"),
person("Lieven","Clement", role="ctb",
email = "[email protected]"))
Description: satuRn provides a higly performant and scalable framework for performing
differential transcript usage analyses. The package consists of three main functions.
The first function, fitDTU, fits quasi-binomial generalized linear models that model
transcript usage in different groups of interest. The second function, testDTU, tests
for differential usage of transcripts between groups of interest. Finally, plotDTU
visualizes the usage profiles of transcripts in groups of interest.
Depends: R (>= 4.1)
Imports: locfdr,
SummarizedExperiment,
BiocParallel,
limma,
pbapply,
ggplot2,
boot,
Matrix,
stats,
methods,
graphics
Suggests:
knitr,
rmarkdown,
testthat,
covr,
BiocStyle,
AnnotationHub,
ensembldb,
edgeR,
DEXSeq,
pasilla,
stageR,
DelayedArray,
fishpond,
data.table,
tximportData
VignetteBuilder: knitr
Collate: 'data.R' 'satuRn-framework.R' 'allGenerics.R'
'accessors.R' 'fitDTU.R' 'testDTU.R' 'plotDTU.R'
License: Artistic-2.0
URL: https://github.com/statOmics/satuRn
BugReports: https://github.com/statOmics/satuRn/issues
Encoding: UTF-8
LazyData: false
RoxygenNote: 7.2.3
biocViews:
Regression,
ExperimentalDesign,
DifferentialExpression,
GeneExpression,
RNASeq,
Sequencing,
Software,
SingleCell,
Transcriptomics,
MultipleComparison,
Visualization