Run GSVA analysis on a SingleCellExperiment object
runGSVA(
inSCE,
useAssay = "logcounts",
resultNamePrefix = NULL,
geneSetCollectionName,
...
)
Input SingleCellExperiment object.
Indicate which assay to use. The default is "logcounts"
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
.
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_geneSetCollectionName_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
#>
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#>