Hi Michael,

I got some question about the tutorial of DESeq2 and I was wondering if you could help me in:

1) normalized metric you use in Deseq is not referring to RPKM or TPKM, but: "counts divided by sample-specific size factors determined by median ratio of gene counts relative to geometric mean per gene" or median of ratio.. so 1) creates a pseudo-reference sample (row-wise geometric mean), 2) calculates ratio of each sample to the reference, 3) calculate the normalization factor for each sample (size factor), 4)calculate the normalized count values using the normalization factor. is that correct?

2) Once I got the DEGs list and I want to take into account whether these differentially transcripts tend to be smaller or larger in transcript size.. I should go back to salmon or kallisto (correct?) approach and run again the analysis or there is a way to get this info out ?

thanks in advance G.

1) Yes

2) If you want to see if the DE genes tend to be smaller or larger in transcript length, you can do the following, just a simple example...

res$length <- rowMeans(assay(dds)[["avgTxLength"]])
table(sig=res$padj < .05, length=cut(log10(res$length), 5))

This assumes you used a tximport pipeline.