runSeuratPCA: runSeuratPCA Computes PCA on the input sce object and stores...

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

runSeuratPCA Computes PCA on the input sce object and stores the calculated principal components within the sce object

Description

runSeuratPCA Computes PCA on the input sce object and stores the calculated principal components within the sce object

Usage

runSeuratPCA(
  inSCE,
  useAssay = "seuratNormData",
  useFeatureSubset = "hvf",
  scale = TRUE,
  reducedDimName = "seuratPCA",
  nPCs = 20,
  seed = 12345,
  verbose = TRUE
)

Arguments

inSCE	(sce) object on which to compute PCA
useAssay	Assay containing scaled counts to use in PCA. Default "seuratNormData".
useFeatureSubset	Subset of feature to use for dimension reduction. A character string indicating a rowData variable that stores the logical vector of HVG selection, or a vector that can subset the rows of inSCE. Default "hvf".
scale	Logical scalar, whether to standardize the expression values using ScaleData. Default TRUE.
reducedDimName	Name of new reducedDims object containing Seurat PCA. Default seuratPCA.
nPCs	numeric value of how many components to compute. Default 20.
seed	Random seed for reproducibility of results. Default NULL will use global seed in use by the R environment.
verbose	Logical value indicating if informative messages should be displayed. Default is TRUE.

Details

For features used for computation, it can be controlled by features or useFeatureSubset. When features is specified, the scaling and dimensionality reduction will only be processed with these features. When features is NULL but useFeatureSubset is specified, will use the features that the HVG list points to. If both parameters are NULL, the function will see if any Seurat's variable feature detection has been ever performed, and use them if found. Otherwise, all features are used.

Value

Updated SingleCellExperiment object which now contains the computed principal components

Examples

data(scExample, package = "singleCellTK")
## Not run: 
sce <- runSeuratNormalizeData(sce, useAssay = "counts")
sce <- runSeuratFindHVG(sce, useAssay = "counts")
sce <- setTopHVG(sce, method = "vst", featureSubsetName = "hvf")
sce <- runSeuratScaleData(sce, useAssay = "counts")
sce <- runSeuratPCA(sce, useAssay = "counts")

## End(Not run)

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