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!

Should be fine with UMI counts. Check meanSdPlot (see DESeq2 workflow) if you want to assess how the transformation did.