Perform PCA on a SingleCellExperiment Object A wrapper to runPCA function to compute principal component analysis (PCA) from a given SingleCellExperiment object.

Source: R/scater_PCA.R

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,
  seed = NULL
)

Arguments

inSCE

Input SingleCellExperiment object.
useAssay

Assay to use for PCA computation. If useAltExp is specified, useAssay has to exist in assays(altExp(inSCE, useAltExp)). Default "logcounts"
useAltExp

The subset to use for PCA computation, usually for the selected.variable features. Default NULL.
reducedDimName

Name to use for the reduced output assay. Default "PCA".
nComponents

Number of principal components to obtain from the PCA computation. Default 50.
scale

Logical scalar, whether to standardize the expression values. Default FALSE.
ntop

Number of top features to use as a further variable feature selection. Default NULL.
seed

Random seed for reproducibility of PCA results.

Value

A SingleCellExperiment object with PCA computation updated in reducedDim(inSCE, reducedDimName).

Examples

data(scExample, package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
sce <- scaterlogNormCounts(sce, "logcounts")
sce <- scaterPCA(sce, "logcounts")