runGSVA: Run GSVA analysis on a SingleCellExperiment object

In compbiomed/singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

Run GSVA analysis on a SingleCellExperiment object

Description

Run GSVA analysis on a SingleCellExperiment object

Usage

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")

compbiomed/singleCellTK documentation built on Oct. 27, 2024, 3:26 a.m.