Calculates contamination scores using a random forest classification
Usage
calcContamination(
cells,
markers = NULL,
num.trees = 100,
verbose = FALSE,
missingReplacement = 0,
assay = "intensities",
cellType = "cellType",
redDimName = "contaminations"
)Arguments
- cells
A SingleCellExperiment or SpatialExperiment with a cellType column as well as marker intensity information corresponding to each cell.
- markers
A vector of markers that proxy a cell's state. If NULL, all markers will be used.
- num.trees
Number of trees to be used in the random forest classifier
- verbose
A logical indicating whether information about the final random forest model should be outputted.
- missingReplacement
A default value to replace missing marker intensities for classification.
- assay
The assay in the SingleCellExperiment object that contains the desired marker expressions.
- cellType
The name of the column in colData that stores the cell types.
- redDimName
The redDimName to store the output in the sce.
Examples
data("kerenSCE")
singleCellDataDistancesContam <- calcContamination(
kerenSCE
)