Generates a doublet score for each cell via doubletFinder

Source: R/doubletFinder_doubletDetection.R

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

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.

Examples

data(scExample, package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
sce <- runDoubletFinder(sce)
#> Sat Mar 18 10:30:38 2023 ... Running 'doubletFinder'
#> Centering and scaling data matrix