Greetings,

I need to analyze data collected from an RNA-seq experiment.  This consists
of comparing two groups (control vs. treatment) and repeated sampling (1
hour, 2 hours, 3 hours).  If this were a univariate problem I know I would
use a 2-way rmANOVA analysis but this is RNA-seq and I have thousands of
variables.  I am very familiar with multiple packages for RNA differential
expression analysis (e.g. DESeq2, edgeR, limma, etc.) but I have been
unable to figure out what the most appropriate way to analyze such data in
this circumstance.  The closest answer I can find within the DESeq2 and
edgeR manuals (limma is somewhat confusing to me) is to place to main
treatment of interest at the end of the design formula, for example:

design(dds) <- formula(~ time + treatment)

Is this what is considered the appropriate way to address repeated measures
in mRNA expression experiments?  Any thoughts are appreciated.

Regards,

-- 
Charles Determan
Integrated Biosciences PhD Candidate
University of Minnesota

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