Dear All,
As I continue my exploration of RNASeq analysis options, it seems that some
approaches are better than others depending on your data-set and goals.
I was wondering if anyone can give me a feeling on when is better to use
Voom vs EdgeR (or DESeq) and whether modelling the distribution is really
that important vs just modelling the variance.

My data set is very noisy, with very low signal and very few differentially
expressed genes, so sensitivity is key to me. I have 4-9 biological
replicates per condition and good depth of coverage
I also have microarrays and extensive qPCR data for the exact same RNA
samples that were sequenced.

Thanks in advance for the suggesitons

-- 
Lucia Peixoto PhD
Postdoctoral Research Fellow
Laboratory of Dr. Ted Abel
Department of Biology
School of Arts and Sciences
University of Pennsylvania

"Think boldly, don't be afraid of making mistakes, don't miss small
details, keep your eyes open, and be modest in everything except your
aims."
Albert Szent-Gyorgyi

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