R/scater_PCA.R
scaterPCA.Rd
Perform PCA on a SingleCellExperiment Object A wrapper to runPCA function to compute principal component analysis (PCA) from a given SingleCellExperiment object.
scaterPCA( inSCE, useAssay = "logcounts", useAltExp = NULL, reducedDimName = "PCA", nComponents = 50, scale = FALSE, ntop = NULL )
inSCE | Input SingleCellExperiment object. |
---|---|
useAssay | Assay to use for PCA computation. If |
useAltExp | The subset to use for PCA computation, usually for the
selected.variable features. Default |
reducedDimName | Name to use for the reduced output assay. Default
|
nComponents | Number of principal components to obtain from the PCA
computation. Default |
scale | Logical scalar, whether to standardize the expression values.
Default |
ntop | Number of top features to use as a further variable feature
selection. Default |
A SingleCellExperiment object with PCA computation
updated in reducedDim(inSCE, reducedDimName)
.
data(scExample, package = "singleCellTK") sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'") sce <- scaterlogNormCounts(sce, "logcounts") sce <- scaterPCA(sce, "logcounts")