Detect doublet cells using scDblFinder.

Source: R/scDblFinder_doubletDetection.R

A wrapper function for scDblFinder. Identify potential doublet cells based on simulations of putative doublet expression profiles. Generate a doublet score for each cell.

runScDblFinder(
  inSCE,
  sample = NULL,
  useAssay = "counts",
  nNeighbors = 50,
  simDoublets = max(10000, ncol(inSCE)),
  seed = 12345,
  BPPARAM = BiocParallel::SerialParam()
)

Arguments

inSCE

A SingleCellExperiment object.

sample

Character vector. Indicates which sample each cell belongs to. scDblFinder will be run on cells from each sample separately.

useAssay

A string specifying which assay in the SCE to use.

nNeighbors

Number of nearest neighbors used to calculate density for doublet detection. Default 50.

simDoublets

Number of simulated doublets created for doublet detection. Default 10000.

seed

Seed for the random number generator. Default 12345.

BPPARAM

A BiocParallelParam object specifying whether the neighbour searches should be parallelized.

Value

A SingleCellExperiment object with the scDblFinder QC outputs added to the colData slot.

Details

This function is a wrapper function for scDblFinder. runScDblFinder runs scDblFinder for each sample within inSCE iteratively. The resulting doublet scores for all cells will be appended to the colData of inSCE.

References

Lun ATL (2018). Detecting doublet cells with scran. https://ltla.github.io/SingleCellThoughts/software/doublet_detection/bycell.html

See also

scDblFinder

Examples

data(scExample, package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
sce <- runScDblFinder(sce)
#> Thu Apr 28 11:28:38 2022 ... Running 'scDblFinder'