Is computing TPM from read count from DEseq2 count matrix necessary?

Question

[theodore.killian]

I am building an RNAseq pipeline using DESeq2 to show transcriptional differences between a group of RNAseq samples starting from a raw count matrix. Is calculating TPM (from the raw count matrix) unnecessary in this context when I already have the normalized counts produced by the DESeq2 analysis?

Similar posts on this forum seem to suggest that calculating TPM is unnecessary Computing TPM from normalized read count from DESEQ

[theodore.killian]

I have obtained the transcript lengths of the genes from my count matrix. Do I use the mean transcript length to calculate TPM?

[predeus]

why do you want to do it manually? Most modern quantification programs (featureCounts, rsem, kallisto, salmon) will do it for you.

It's more complicated than just transcript length (and what is mean transcript length?) - the formula is

transcript length - mean fragment length + 1

(and I'm not sure what happens for transcripts of length smaller than FL)

Answer 1

[predeus]

Depends on what you want to do with it. It's not needed for differential gene expression (and in fact should not be used for DE)

TPMs are used for different things - like clustering, classification of gene expression strength, etc