runScanpyNormalizeData Wrapper for NormalizeData() function from scanpy library Normalizes the sce object according to the input parameters

runScanpyNormalizeData Wrapper for NormalizeData() function from scanpy library Normalizes the sce object according to the input parameters

runScanpyNormalizeData(
  inSCE,
  useAssay,
  targetSum = 10000,
  maxFraction = 0.05,
  normAssayName = "scanpyNormData"
)

Arguments

inSCE

(sce) object to normalize

useAssay

Assay containing raw counts to use for normalization.

targetSum

If NULL, after normalization, each observation (cell) has a total count equal to the median of total counts for observations (cells) before normalization. Default 1e4

maxFraction

Include cells that have more counts than max_fraction of the original total counts in at least one cell. Default 0.05

normAssayName

Name of new assay containing normalized data. Default scanpyNormData.

Value

Normalized SingleCellExperiment object

Examples

data(scExample, package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
rownames(sce) <- rowData(sce)$feature_name
if (FALSE) {
sce <- runScanpyNormalizeData(sce, useAssay = "counts")
}