DESeq2 package for differential analysis of count data

Description

The main functions for differential analysis are DESeq and results. See the examples at DESeq for basic analysis steps. Two transformations offered for count data are the "regularized logarithm", rlog, and varianceStabilizingTransformation. For more 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 support questions should be posted to the Bioconductor support site: http://support.bioconductor.org.

Author(s)

Michael Love, Wolfgang Huber, Simon Anders

References

DESeq2 reference:

Michael I Love, Wolfgang Huber, Simon Anders: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014, 15:550. http://dx.doi.org/10.1186/s13059-014-0550-8

DESeq reference:

Simon Anders, Wolfgang Huber: Differential expression analysis for sequence count data. Genome Biology 2010, 11:106. http://dx.doi.org/10.1186/gb-2010-11-10-r106

Results