Dear Bioconductor community,
First of all, thank you for this forum that helped me many times during my PhD years. This is the first time I'm posting a question, but I've been following the forum for a long time now.
My problem is the following : I would like to introduce bias coefficients into DESeq2, before differential expression analysis.
Basically, what I would like to do is to multiply all my raw counts in a given sample by a coefficient k.
So let's say I have two samples A and B, for two genes, a and b. I would like to transform my initial count matrix
A B
a x1 x2
b x3 x4
in
A B
a x1*k1 x2*k2
b x3*k1 x4*k2
However, my current problem is that would only be accounted as sequecing depth, thus normalized by DESeq2. Is there a way to introduce a bias after normalization ? Does that even make sense to use DESeq2 ?
For those interested in why, it would be to use DESeq2 to compare absolute production of RNA (let's say two cell type population, with different abundance, thus not only comparing the relative enrichment of a gene in each cell type, but the total enrichment of that gene in a mix of these two cells with known cell type abundance).
Thank you very much for your help and kind support and excuse me if my question is not perfectly posed (yet!),
David Benacom
