Hi recently there has been some publication on the importance of GC and length bias ( Mandelboum et al, 2019, PLOS) . I'm looking into how to do this and came across packages like EDAseq. So it looks pretty straightforward with something like this.
dataOffset <- withinLaneNormalization(data,"gc", which="full",offset=TRUE)
this provide two slots, one for the normalized counts and the other for the offsets. I'm wondering if I can then use the dataOffset normalize count, say normalized_count as input for TMM normalization follow with voom. Would this work, something like.
y.df <- calcNormFactors( y.normalized_count , method = "TMM" ) voom <- voom(y.ydf )
and then just do the limma DGE?