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Compute expression-weighted centered scaled ranks (EWCSR)

Source: R/ewcsr.sparse.R
ewcsr.sparse.Rd

Computes expression-weighted centered scaled ranks for a sparse or dense expression matrix, calculated per column (cell).

Usage

ewcsr.sparse(mat, num_threads = -1L)

Arguments

mat

A matrix with features (genes) as rows and cells or samples as columns.

num_threads

Integer; number of threads to use. The default is -1 which uses all available cores.

Value

A matrix of EWCSR-transformed values with the same dimensions as mat.

Details

EWCSR transformation emphasizes relatively high and low expression features within each cell while accounting for expression magnitude. The output matrix retains the same dimensions as the input.

See also

gini.ewcsr.fs, markoCell

Examples

utils::data("pbmc_small", package = "SeuratObject")

mat <- SeuratObject::LayerData(
  pbmc_small,
  assay = "RNA",
  layer = "counts"
)

ewcsr_mat <- ewcsr.sparse(mat, num_threads = 1)