The Easiest/Fastest Way To Get From Bam To Tpm Or Rpkm

Question

[Nick]

I have already aligned all my RNA-seq samples using tophat2. I've done the differential analysis using htseq-count and edgeR. I would like to get rpkm and tpm metrics. What is the easiest way to do that using the output of tophat2, htseq-count and edgeR? I also have the reference GTF. So, please, recommend a tool or a workflow that would take me to TPKM or RPKM in less than a day - I have a machine with 32GB RAM and 8 cores and my study comprises 24 samples.

Answer 1

[Madelaine Gogol]

Edger rpkm() function?

[Nick]

Thanks - this would be really neat. I just checked the manual but can't quite understand how to produce it from a DGEList object. Can you, perhaps, give an example?

[Nick]

I also saw that logCPM (counts per million) is part of the topTags object but I don't understand how to interpret it. Is there a way to derive RPKM from it?

[Madelaine Gogol]

Did you try ?rpkm

rpkm(x, gene.length, normalized.lib.sizes=TRUE, log=FALSE, prior.count=0.25)

Where x is a DGElist

Answer 2

[dfernan]

Easiest means wrong in this case, since one cannot possibly get a right estimate for RPKMs in an RNA-Seq experiment without proper handle of multiple alignments. I'd say the easiest and still right way to do it is to use Express/Cufflinks/RSEM/etc. - they produce RPKM estimates, and RSEM produces RPKM/TPM estimates - anything else without handling of multiple alignments may be easy but it's just wrong...

You can also get RPKM estimates and transform them to TPM estimates