To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("edgeR")
In most cases, you don't need to download the package archive at all.
Bioconductor version: Release (3.4)
Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, SAGE and CAGE.
Author: Yunshun Chen <yuchen at wehi.edu.au>, Aaron Lun <alun at wehi.edu.au>, Davis McCarthy <dmccarthy at wehi.edu.au>, Xiaobei Zhou <xiaobei.zhou at uzh.ch>, Mark Robinson <mark.robinson at imls.uzh.ch>, Gordon Smyth <smyth at wehi.edu.au>
Maintainer: Yunshun Chen <yuchen at wehi.edu.au>, Aaron Lun <alun at wehi.edu.au>, Mark Robinson <mark.robinson at imls.uzh.ch>, Davis McCarthy <dmccarthy at wehi.edu.au>, Gordon Smyth <smyth at wehi.edu.au>
Citation (from within R,
enter citation("edgeR")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("edgeR")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("edgeR")
edgeR Vignette | ||
edgeRUsersGuide.pdf | ||
Reference Manual | ||
Text | NEWS |
Follow Installation instructions to use this package in your R session.
Package Source | edgeR_3.16.5.tar.gz |
Windows Binary | edgeR_3.16.5.zip (32- & 64-bit) |
Mac OS X 10.9 (Mavericks) | edgeR_3.16.5.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/edgeR/tree/release-3.4 |
Package Short Url | http://bioconductor.org/packages/edgeR/ |
Package Downloads Report | Download Stats |
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