runDoubletFinder: Generates a doublet score for each cell via doubletFinder

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

Generates a doublet score for each cell via doubletFinder

Description

Uses doubletFinder to determine cells within the dataset suspected to be doublets.

Usage

runDoubletFinder(
  inSCE,
  sample = NULL,
  useAssay = "counts",
  seed = 12345,
  seuratNfeatures = 2000,
  seuratPcs = seq(15),
  seuratRes = 1.5,
  formationRate = 0.075,
  nCores = NULL,
  verbose = FALSE
)

Arguments

inSCE	inSCE A SingleCellExperiment object.
sample	Character vector or colData variable name. Indicates which sample each cell belongs to. Default NULL.
useAssay	A string specifying which assay in the SCE to use. Default "counts".
seed	Seed for the random number generator, can be set to NULL. Default 12345.
seuratNfeatures	Integer. Number of highly variable genes to use. Default 2000.
seuratPcs	Numeric vector. The PCs used in seurat function to determine number of clusters. Default 1:15.
seuratRes	Numeric vector. The resolution parameter used in Seurat, which adjusts the number of clusters determined via the algorithm. Default 1.5.
formationRate	Doublet formation rate used within algorithm. Default 0.075.
nCores	Number of cores used for running the function. Default NULL.
verbose	Boolean. Wheter to print messages from Seurat and DoubletFinder. Default FALSE.

Value

SingleCellExperiment object containing the doublet_finder_doublet_score variable in colData slot.

See Also

runCellQC, plotDoubletFinderResults

Examples

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

compbiomed/singleCellTK documentation built on Feb. 10, 2024, 3:32 a.m.