edgeR

Empirical analysis of digital gene expression data in R

Bioconductor version: 2.8

Differential expression analysis of RNA-seq and digital gene expression profiles with biological replication. Uses empirical Bayes estimation and exact tests based on the negative binomial distribution. Also useful for differential signal analysis with other types of genome-scale count data.

Author: Mark Robinson <mrobinson at wehi.edu.au>, Davis McCarthy <dmccarthy at wehi.edu.au>, Gordon Smyth <smyth at wehi.edu.au>

Maintainer: Mark Robinson <mrobinson at wehi.edu.au>, Davis McCarthy <dmccarthy at wehi.edu.au>, Gordon Smyth <smyth at wehi.edu.au>

To install this package, start R and enter:

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

To cite this package in a publication, start R and enter:

    citation("edgeR")

Documentation

PDF R Script edgeR User's Guide
PDF edgeR_case_study_Li_MDSplot.pdf
PDF edgeR_case_study_longSAGE_MDSplot.pdf
PDF edgeR_case_study_Tuch_MDSplot.pdf
PDF   Reference Manual

Details

biocViews Bioinformatics, DifferentialExpression, SAGE, HighThroughputSequencing, RNAseq
Depends R (>= 2.3.0), methods
Imports limma
Suggests MASS, statmod, splines
System Requirements
License LGPL (>= 2)
URL
Depends On Me oneChannelGUI
Imports Me ArrayExpressHTS, rnaSeqMap
Suggests Me goseq, leeBamViews
Version 2.2.6
Since Bioconductor 2.3 (R-2.8)

Package Downloads

Package Source edgeR_2.2.6.tar.gz
Windows Binary edgeR_2.2.6.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary edgeR_2.2.6.tgz
Package Downloads Report Download Stats

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