Run GSVA analysis on a SingleCellExperiment object
runGSVA( inSCE, useAssay = "logcounts", resultNamePrefix = NULL, geneSetCollectionName, ... )
inSCE | Input SingleCellExperiment object. |
---|---|
useAssay | Indicate which assay to use. The default is "logcounts" |
resultNamePrefix | Character. Prefix to the name the VAM results which will be stored in the reducedDim slot of |
geneSetCollectionName | Character. The name of the gene set collection to use. parameter. |
... | Parameters to pass to gsva() |
A SingleCellExperiment object with pathway activity scores from GSVA stored in reducedDim
as GSVA__NameOfTheGeneset_Scores
.
data(scExample, package = "singleCellTK") sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'") sce <- scaterlogNormCounts(sce, assayName = "logcounts") gs1 <- rownames(sce)[seq(10)] gs2 <- rownames(sce)[seq(11,20)] gs <- list("geneset1" = gs1, "geneset2" = gs2) sce <- importGeneSetsFromList(inSCE = sce,geneSetList = gs, by = "rownames") sce <- runGSVA(inSCE = sce, geneSetCollectionName = "GeneSetCollection", useAssay = "logcounts")#> Estimating GSVA scores for 2 gene sets. #> Estimating ECDFs with Gaussian kernels #> | | | 0% | |=================================== | 50% | |======================================================================| 100% #>