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