edgeR-package: Empirical analysis of digital gene expression data in R
Description
edgeR is a package for the analysis of digital gene expression data arising from RNA sequencing technologies such as SAGE, CAGE, Tag-seq or RNA-seq, with emphasis on testing for differential expression.
Particular strengths of the package include the ability to estimate biological variation between replicate libraries, and to conduct exact tests of significance which are suitable for small counts.
The package is able to make use of even minimal numbers of replicates.
The supplied counts are assumed to be those of genes in a RNA-seq experiment.
However, counts can be supplied for any genomic feature of interest, e.g., tags, transcripts, exons, or even arbitrary intervals of the genome.
An extensive User's Guide is available, and can be opened by typing edgeRUsersGuide() at the R prompt.
Detailed help pages are also provided for each individual function.
The edgeR package implements original statistical methodology described in the publications below.References
Robinson MD and Smyth GK (2007). Moderated statistical tests for
assessing differences in tag abundance. Bioinformatics 23, 2881-2887
Robinson MD and Smyth GK (2008). Small-sample estimation of negative
binomial dispersion, with applications to SAGE data. Biostatistics,
9, 321-332
Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor
package for differential expression analysis of digital gene
expression data. Bioinformatics 26, 139-140
McCarthy, DJ, Chen, Y, Smyth, GK (2012).
Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.
Nucleic Acids Research 40, 4288-4297.
Lund, SP, Nettleton, D, McCarthy, DJ, Smyth, GK (2012).
Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates.
Statistical Applications in Genetics and Molecular Biology. (Accepted 31 July 2012)