Hello,
I am doing my first NGS analysis and I am working with single cell RNA seq data. I want to be sure if its ok to use TPM for the downstream analysis (which I am planing to start with SINCERA pipeline )
thanks in advance for your help, Anna
It depends.. If you want to analyze differential expression with packages such as DESeq2 oe EdgeR, you need to provide the raw counts, since these packages has their own normalization methods
There are recommendations on how to use DESeq2 for single-cell applications which involves the zinbwave package. http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#recommendations-for-single-cell-analysis
The community is generally more used to FPKM but the author of FPKM itself said that we should move on because it is biased (ref).
Also, you can convert FPKM to TPM using a formula. And if you can't access that formula, I also report it in one of my papers (see methods section "ΔXT/FT expression profile").
I would really analyse both and take a conclusion after seeing both values for each gene.
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version 2.3.6
After some reading I should use TPM. So I have a count matrix( reads per transcript or fragments per transcript) derived from featureCounts (subread package) and I want to normalize in order to have TPM and afterwards to use this as an input to SINCERA pipeline for single cell transcriptome analysis
neither of them is perfect.