To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("DESeq2")

In most cases, you don't need to download the package archive at all.

DESeq2

Differential gene expression analysis based on the negative binomial distribution

Bioconductor version: 2.13

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 (MPIMG Berlin), Simon Anders, Wolfgang Huber (EMBL Heidelberg)

Maintainer: Michael Love <michaelisaiahlove at gmail.com>

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

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("DESeq2")

Documentation

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

browseVignettes("DESeq2")

 

PDF R Script Analyzing RNA-Seq data with the "DESeq2" package
PDF vst.pdf
PDF   Reference Manual
Text   NEWS

Details

biocViews ChIPseq, DifferentialExpression, HighThroughputSequencing, RNAseq, SAGE, Software
Version 1.2.10
In Bioconductor since BioC 2.12 (R-3.0)
License GPL (>= 3)
Depends GenomicRanges, IRanges, Rcpp (>= 0.10.1), RcppArmadillo (>= 0.3.4.4)
Imports BiocGenerics(>= 0.7.5), methods, locfit, genefilter, RColorBrewer, lattice
Suggests RUnit, Biobase, parathyroidSE, pasilla(>= 0.2.10), vsn, gplots, BiocStyle
System Requirements
URL
Depends On Me
Imports Me HTSFilter, ReportingTools
Suggests Me BiocGenerics, DiffBind, gage

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source DESeq2_1.2.10.tar.gz
Windows Binary DESeq2_1.2.10.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) DESeq2_1.2.10.tgz
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