Run GSVA analysis on a SingleCellExperiment object

runGSVA(
  inSCE,
  useAssay = "logcounts",
  resultNamePrefix = NULL,
  geneSetCollectionName,
  ...
)

Arguments

inSCE: Input SingleCellExperiment object.
useAssay: Indicate which assay to use. The default is "logcounts"
resultNamePrefix: Character. Prefix to the name the GSVA results which will be stored in the reducedDim slot of inSCE. The names of the output matrix will be resultNamePrefix_Scores. If this parameter is set to NULL, then "GSVA_geneSetCollectionName_" will be used. Default NULL.
geneSetCollectionName: Character. The name of the gene set collection to use.
...: Parameters to pass to gsva()

Value

A SingleCellExperiment object with pathway activity scores from GSVA stored in reducedDim as GSVA_geneSetCollectionName_Scores.

Examples

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")
#> Tue Jun 28 22:07:07 2022 ... Running GSVA
#> Estimating GSVA scores for 2 gene sets.
#> Estimating ECDFs with Gaussian kernels
#> 
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#>