runScanpyNormalizeData: runScanpyNormalizeData Wrapper for NormalizeData() function...

In compbiomed/singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

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

Description

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

Usage

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
## Not run: 
sce <- runScanpyNormalizeData(sce, useAssay = "counts")

## End(Not run)

compbiomed/singleCellTK documentation built on Oct. 27, 2024, 3:26 a.m.