General QC for liger object

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)
)

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.

Value

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

Examples

pbmc <- runGeneralQC(pbmc)
#> ℹ calculating QC for dataset "ctrl"
#> ✔ calculating QC for dataset "ctrl" ... done
#> 
#> ℹ calculating QC for dataset "stim"
#> ✔ calculating QC for dataset "stim" ... done
#>