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() )
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 |
A SingleCellExperiment object with the scDblFinder QC outputs added to the colData slot.
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
.
Lun ATL (2018). Detecting doublet cells with scran. https://ltla.github.io/SingleCellThoughts/software/doublet_detection/bycell.html
data(scExample, package = "singleCellTK") sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'") sce <- runScDblFinder(sce)#>