runGeneralQC: General QC for liger object

Description

Calculate number of UMIs, number of detected features and percentage of feature subset (e.g. mito) expression per cell.

Usage

runGeneralQC(
  object,
  mito = TRUE,
  ribo = TRUE,
  hemo = TRUE,
  features = NULL,
  pattern = NULL,
  useDatasets = NULL,
  chunkSize = 1000,
  verbose = getOption("ligerVerbose", TRUE)
)

Value

Updated object with nUMI, nGene updated in cellMeta(object), as well as expression percentage value for each feature subset.

Arguments

object: liger object with rawData available in each ligerDataset embedded
mito, ribo, hemo: Whether to calculate the expression percentage of mitochondrial, ribosomal or hemoglobin genes, respectively. Default TRUE.
features: Feature names matching the feature subsets that users want to calculate the expression percentage with. A vector for a single subset, or a named list for multiple subset. Default NULL.
pattern: Regex patterns for matching the feature subsets that users want to calculate the expression percentage with. A vector for a single subset, or a named list for multiple subset. Default NULL.
useDatasets: A character vector of the names, a numeric or logical vector of the index of the datasets to be included for QC. Default NULL performs QC on all datasets.
chunkSize: Integer number of cells to include in a chunk when working on HDF5 based dataset. Default 1000
verbose: Logical. Whether to show information of the progress. Default getOption("ligerVerbose") or TRUE if users have not set.

Examples

Run this code

pbmc <- runGeneralQC(pbmc)

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