runDoubletFinder {singleCellTK} | R Documentation |
Uses doubletFinder to determine cells within the dataset suspected to be doublets.
runDoubletFinder( inSCE, useAssay = "counts", sample = NULL, seed = 12345, seuratNfeatures = 2000, seuratPcs = seq(15), seuratRes = 1.5, formationRate = 0.075, nCores = NULL, verbose = FALSE )
inSCE |
Input SingleCellExperiment object. Must contain a counts matrix |
useAssay |
Indicate which assay to use. Default "counts". |
sample |
Numeric vector. Each cell will be assigned a sample number. |
seed |
Seed for the random number generator. 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. |
verbose |
Boolean. Wheter to print messages from Seurat and DoubletFinder. Default FALSE. |
SingleCellExperiment object containing the 'doublet_finder_doublet_score'.
data(scExample, package = "singleCellTK") sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'") sce <- runDoubletFinder(sce)