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.
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