runBcds {singleCellTK} | R Documentation |
A wrapper function for bcds. Annotate
doublets/multiplets using a binary classification approach to discriminate
artificial doublets from original data. Generate a doublet
score for each cell. Infer doublets if estNdbl
is TRUE
.
runBcds( inSCE, sample = NULL, seed = 12345, ntop = 500, srat = 1, verb = FALSE, retRes = FALSE, nmax = "tune", varImp = FALSE, estNdbl = FALSE, useAssay = "counts" )
inSCE |
A SingleCellExperiment object.
Needs |
sample |
Character vector. Indicates which sample each cell belongs to. bcds will be run on cells from each sample separately. If NULL, then all cells will be processed together. Default NULL. |
seed |
Seed for the random number generator. Default 12345. |
ntop |
See bcds for more information. Default |
srat |
See bcds for more information. Default |
verb |
See bcds for more information. Default |
retRes |
See bcds for more information. Default |
nmax |
See bcds for more information. Default |
varImp |
See bcds for more information. Default |
estNdbl |
See bcds for more information. Default |
useAssay |
A string specifying which assay in the SCE to use. |
A SingleCellExperiment object with bcds output appended to the colData slot. The columns include bcds_score and optionally bcds_call. Please refer to the documentation of bcds for details.
data(scExample, package = "singleCellTK") sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'") sce <- runBcds(sce)