DESeq2-package: DESeq2 package for differential analysis of count data

Description Details Author(s) References


The DESeq2 package is designed for normalization, visualization, and differential analysis of high-dimensional count data. It makes use of empirical Bayes techniques to estimate priors for log fold change and dispersion, and to calculate posterior estimates for these quantities.


The main functions are:

For detailed information on usage, see the package vignette, by typing vignette("DESeq2"), or the workflow linked to on the first page of the vignette.

All software-related questions should be posted to the Bioconductor Support Site:

The code can be viewed at the GitHub repository, which also lists the contributor code of conduct:


Michael Love, Wolfgang Huber, Simon Anders


Love, M.I., Huber, W., Anders, S. (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15:550.

DESeq2 documentation built on Feb. 22, 2021, 10 a.m.