Dear All,

I have RNAseq counts for 400 human donors. This is a random sampling of human subjects from a population-wide study. I am not interested in differential expression of genes between certain groups. There are differences in sequence reads because of library size therefore I need to normalize the counts.

I have been reading the postings on this list regarding the normalization methods in DEseq and edgeR. I looked at the reference manuals of both of these packages. I understand that they both use different normalization approaches. My understanding is that while both approaches use the sample information (i.e. whether they are from control or treatment condition) in order to create a list object as a first step, this information is not used in the normalization step but only in the differential expression analysis step. Is this correct?

I am also curious to hear other's opinions regarding different approaches for a study design like mine. Perhaps I have been looking at the wrong places but the papers I found in the literature seem to be concerned with differential expression of transcripts between groups.

Mete

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