RPM data analysis with DESeq2

Question

[ruhollah]

I have a table of RPM data for gene expressions of all human genes in two groups of patients. (each group includes several samples)

I am going to use DESeq2 to explore if there is any gene whose expression significantly changes between two groups.

DESeq2, however, seems like accepts only nu-normalized counts for the RNA seq. Is there a way to feed the DESeq2 with RPM data?

[Kevin Blighe]

Cross-posted on Bioconductor: https://support.bioconductor.org/p/120164/

Answer 1

[manuel.belmadani]

I think DESeq2 expects counts, so passing it some normalized values (like TPM, RPKM, FPKM) is probably not optimal.

Do you have RPKM, or RPM (Reads-per-million)? If you have the latter, you can convert them to RPKM by dividing each RPM by the length of the gene in kilobases. If you want to get counts, you could multiply your RPM by (Number of reads in Sample / 1 000 000) and that should give you counts, which you should be able to use with DESeq. Make sure you know whether you have RPMs or RPKMs.

See also: https://support.bioconductor.org/p/56275/#56299, which suggests converting back to count preferably, or if you're stuck with RPKM then use limma instead of DESeq2.

Also, handy reference on RPKM, FPKM, TPM measures: https://www.rna-seqblog.com/rpkm-fpkm-and-tpm-clearly-explained/

[ruhollah]

Thank you so much for clarification! I got the count data. I will work on it. This is my first experience w/ DESeq though