Hello, If I have three conditions with 3 replicates each. And If I want to check the expression of a particular Gane A across these conditions, what normalization technique would be better FPKM/TPM? And can we use these normalized counts FPKM/TPM counts for performing differential expression study, with DESeq2 / limma?
The TPM is always recommended over FPKM / RPKM, because in the later case, the normalized counts are not comparable across the samples
https://hbctraining.github.io/DGE_workshop/lessons/02_DGE_count_normalization.html
I agree that TPM is prefered - but generally I would say that is due to the normalization to effective transcript length (instead of annotated) and other sequncing biases.
Furthermore FPKM/RPKM are only unstrustworthy in cases where you have a global shift in the length distribution of transcripts - which in my experience is quite rare.
In fact, it is FPKM / RPKM that are rarely suitable for differential expression analysis because there is no cross-sample normalisation performed when deriving these units..
Please read this: A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis
Also, by Harold Pimental: What the FPKM? A review of RNA-Seq expression units
could you clarify what do you mean by that?