I have raw read count of two groups of patients I want to normalize this matrix in a way getting TMM or geometric mean values by DESeq2 how can I do that?
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zizigolu
1 answer
Hello, this should return what you need:
counts(dds, normalised = TRUE)
Kevin
Good point. Probably just normalized
I just wanted to point out for the original poster's knowledge that only edgeR uses TMM normalization.
Perhaps take a look at the output of ?DESeq2::counts
normalized: logical indicating whether or not to divide the counts by the size factors or normalization factors before returning (normalization factors always preempt size factors)
Thank you so much
In GSEA manual says
Normalizing RNA-seq quantification to support comparisons of a feature's expression levels across samples is important for GSEA. Normalization methods (such as, TMM, geometric mean) which operate on raw counts data should be applied prior to running GSEA. Tools such as DESeq2 can be made to produce properly normalized data (normalized counts) which are compatible with GSEA
So I have two groups (n=9 versus n=24)
I put my raw counts matrix in this formula
dge <- DGEList(M)
dge <- calcNormFactors(dge)
logCPM <- cpm(dge, log=TRUE)
Does logCPM gives proper input for GSEA?
I asked this in Bioconductor and Gordon Smith believes this is fine
https://support.bioconductor.org/p/133174/ Honestly I am not certain
Indeed, yes, logCPM is okay for GSEA. There is no problem here.
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