I need an opinion about either using normalized counts from EDASeq or raw counts with offset values of EDASeq in edgeR GLM for differential expression. I read edgeR manual where it says:
"The correction factors may take the form of scaling factors for the library sizes, such as computed by calcNormFactors, which are then used to compute the effective library sizes. Alternatively, gene-specific correction factors can be entered into the glm functions of edgeR as offsets."
Also it is mentioned that estimateCommonDisp and estimateTagwiseDisp require the library sizes to be equal for all samples for exactTest. Is this applicable to GLM dispersion estimation as well? If so then it seems I would have to use calcNormFactors() if the library sizes are not equal whether normalized offset values are provided or not. But then it is also mentioned that alternative to calcNormFactors are offset values other software such as cqn or EDASeq. How should I run differential expression on values normalized by EDASeq? Should I give raw values with offset values or normalized counts from EDASeq in edgeR?