GSVA Analysis Ouput Array gives lesser gene sets than original gene set array
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2.2 years ago
amit15013 • 0

Hi

I am doing gsva analysis on pathways gene sets which consists of 186 gene set. When i run gsva analysis on my dataset it returns only 168 gene sets. How do i get to know which gene set has been returned as there is not naming in the final output array.

Thank you

GSVA • 672 views
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What software/package are you using?

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Ciao Pietro. S/He is using GSVA: https://bioconductor.org/packages/release/bioc/html/GSVA.html

amit15013, please show all of the commands that you are using.

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Hi

This is the code i am using

exprs <- as.matrix(read.table("~/velocyto/velocity_matrix_output.csv", header=TRUE, sep=",",row.names=1,as.is=TRUE))
gsva_set<- ExpressionSet(assayData=exprs)
gsva_analysis <- gsva(gsva_set@assayData$exprs,our_genes$genesets,min.sz=0, max.sz=500, verbose=TRUE)


This returns only 168 gene sets and not 186. Also it doesn't return the names of the gene sets which are processed.

Thank you

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our_genes should be a named list, right? - are the names assigned?

Even though you have min.sz=0, I think that it is possible that GSVA will not return gene sets that do not have any match genes - not 100% sure, though.

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Yes, our_genes prints the names of the pathways as well as the genes present in it.

True, even though it has min.sz=0 it is returnig only 168 gene set and not 186.

Thank you

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Best thing, then, is to infer the ones that are not returned and then investigate why. Not sure about the names issued - I recently used my own curated gene set with GSVA and it returned names.

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Hey, I had to wait until I got home. I just checked and, indeed, the names are being carried through. Take a look:

names(genesets)
[1] "C1_mean_UMI"  "C2_mean_UMI"  "C3_mean_UMI"  "C4_mean_UMI"  "C5_mean_UMI"
[6] "C6_mean_UMI"  "C7_mean_UMI"  "C8_mean_UMI"  "C9_mean_UMI"  "C10_mean_UMI"
...

topMatrixGSVA <- gsva(vstMatrix, genesets, method="gsva", min.sz=5, max.sz=999999, abs.ranking=FALSE, verbose=TRUE)
Estimating GSVA scores for 29 gene sets.
Computing observed enrichment scores
Estimating ECDFs with Gaussian kernels
Using parallel with 4 cores
|=============================================================         |  88%

rownames(topMatrixGSVA)
[1] "C1_mean_UMI"  "C2_mean_UMI"  "C3_mean_UMI"  "C4_mean_UMI"  "C5_mean_UMI"
[6] "C6_mean_UMI"  "C7_mean_UMI"  "C8_mean_UMI"  "C9_mean_UMI"  "C10_mean_UMI"
...


Are you sure that your gene-sets are in a named list? Which version of GSVA are you using? - I have GSVA_1.30.0

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Maybe some gene sets are larger than 500 genes (max.sz=500)?

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No i checked that. Max size is 93.