DESeq2

This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see DESeq2.

Differential gene expression analysis based on the negative binomial distribution

Bioconductor version: 3.14

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Author: Michael Love [aut, cre], Constantin Ahlmann-Eltze [ctb], Kwame Forbes [ctb], Simon Anders [aut, ctb], Wolfgang Huber [aut, ctb], RADIANT EU FP7 [fnd], NIH NHGRI [fnd], CZI [fnd]

Maintainer: Michael Love <michaelisaiahlove at gmail.com>

Citation (from within R, enter citation("DESeq2")):

Installation

To install this package, start R (version "4.1") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
BiocManager::install("DESeq2")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("DESeq2")

Analyzing RNA-seq data with DESeq2 HTML R Script

Reference Manual PDF

NEWS Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews Bayesian, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, ImmunoOncology, Normalization, PrincipalComponent, RNASeq, Regression, Sequencing, Software, Transcription

Version 1.34.0

In Bioconductor since BioC 2.12 (R-3.0) (11 years)

License LGPL (>= 3)

Depends S4Vectors(>= 0.23.18), IRanges, GenomicRanges, SummarizedExperiment(>= 1.1.6)

Imports BiocGenerics(>= 0.7.5), Biobase, BiocParallel, genefilter, methods, stats4, locfit, geneplotter, ggplot2, Rcpp (>= 0.11.0)

System Requirements

URL https://github.com/mikelove/DESeq2

Suggests testthat, knitr, rmarkdown, vsn, pheatmap, RColorBrewer, apeglm, ashr, tximport, tximeta, tximportData, readr, pbapply, airway, pasilla(>= 0.2.10), glmGamPoi, BiocManager

Linking To Rcpp, RcppArmadillo

Enhances

Depends On Me DEWSeq, DEXSeq, metaseqR2, rgsepd, rnaseqDTU, rnaseqGene, SeqGSEA, TCC, tRanslatome