View source: R/scds_doubletdetection.R
runCxdsBcdsHybrid | R Documentation |
A wrapper function for cxds_bcds_hybrid. 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
.
runCxdsBcdsHybrid(
inSCE,
sample = NULL,
seed = 12345,
nTop = 500,
cxdsArgs = list(),
bcdsArgs = list(),
verb = FALSE,
estNdbl = FALSE,
force = FALSE,
useAssay = "counts"
)
inSCE |
A SingleCellExperiment object.
Needs |
sample |
Character vector. Indicates which sample each cell belongs to. cxds_bcds_hybrid 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 |
The number of top varialbe genes to consider. Used in both |
cxdsArgs |
See cxds_bcds_hybrid for more information. Default |
bcdsArgs |
See cxds_bcds_hybrid for more information. Default |
verb |
See cxds_bcds_hybrid for more information. Default |
estNdbl |
See cxds_bcds_hybrid for more information. Default |
force |
See cxds_bcds_hybrid for more information. Default |
useAssay |
A string specifying which assay in the SCE to use. |
A SingleCellExperiment object with cxds_bcds_hybrid output appended to the colData slot. The columns include hybrid_score and optionally hybrid_call. Please refer to the documentation of cxds_bcds_hybrid for details.
data(scExample, package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
sce <- runCxdsBcdsHybrid(sce)
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