GSVA function
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@7e6a2774
Last seen 6 weeks ago
Italy

I want to do some analysis with the GSVA function in R, but I want to ask you if the matrix should be just normalized with DESeq2 or also log trasformed. I did this passage:


dds_campione <- DESeqDataSetFromMatrix(countData=raw, 
                                       colData=condition_breakfast, 
                                       design=~ Campione)

smallestGroupSize <- 3
keep <- rowSums(counts(dds_campione) >= 10) >= smallestGroupSize
dds_campione <- dds_campione[keep,]

matriceFiltrata <- counts(dds_campione, normalized = TRUE)

risultati_ssGSVA_temba <- gsva(expr = as.matrix(matriceFiltrata), 
                       gset.idx.list = tebua)

Is it ok or I also have to log trasformed the matrix before the last passage? Thank you

DESeq2 GSVA ssGSEA • 327 views
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Robert Castelo ★ 3.3k
@rcastelo
Last seen 1 day ago
Barcelona/Universitat Pompeu Fabra

Hi,

We recommend to input normalized expression values in logarithmic scale to GSVA. We also recommend to use the latest release of the GSVA package in Bioconductor 3.19, and in that case, you cannot anymore call the gsva() function in the way you're doing it in your code, you should build first a parameter object, please consult the vignette of GSVA and do not hesitate to ask here if you have questions on how to proceed calling gsva().

cheers,

robert.

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When I log trasform my matrix after the DESeq2 normalization, I have some negative value, should I add a 1 to all my matrix?

Thank you

Michela

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No, negative values may occur after log transformation when the log(x) is taken from a positive number x with 0 < x < 1, and therefore expression level quantities such as log CPM or log TPM units of expression may be negative when CPM or TPM units are between 0 and 1, which arise from low levels of expression, but GSVA has no problem with that. What it is also recommended in general, for analysis such as differentialy expression, but also for GSVA, is to filter out lowly-expressed genes.

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