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Hello, Is it correct to use the variance stabilizing transformation from DESeq2 to normalize bulk UMI counts? I have a matrix samplesXgenes with UMI counts and i was wondering if DESeq2 can handle UMI counts too or only read counts.

This is what i'm simply doing:

```
dds <- DESeqDataSetFromMatrix(countData=as.matrix(umi_matrix), colData=targets, design=~subtype)
dds <- dds[rowSums(counts(dds))>=10,]
vsd <- varianceStabilizingTransformation(dds, blind=F)
```

Thanks in advance for any help!

Thank you for the answer!!

I'm working on two datasets, and while the meanSdPlot of the first one looks good, the second one has a different trend. Do you think it can be linked to the fact that they're UMI counts?

Both of these look pretty good to me. Compare to log(x+1)