Feature selection using Gini coefficient on EWCSR-transformed data

Performs feature selection based on the Gini inequality coefficient computed on expression-weighted centered scaled rank (EWCSR) data.

Usage

gini.ewcsr.fs(
  mat,
  gini_thresh = 0.5,
  ewcsr_high_thresh = NULL,
  ewcsr_low_thresh = NULL,
  noise_thresh = NULL,
  num_threads = -1
)

Arguments

mat

A matrix with features as rows and cells as columns.

gini_thresh

Numeric; Gini threshold for selecting specific features.

ewcsr_high_thresh

Numeric; upper EWCSR threshold for binarization. EWCSR values higher than this threshold will be converted to TRUE.

ewcsr_low_thresh

Numeric; lower EWCSR threshold for binarization. EWCSR values lower than this threshold will be converted to TRUE.

noise_thresh

Integer; minimum number of cells required for a feature to be retained.

num_threads

Integer; number of threads to use. -1 uses all available cores.

Value

A list containing specific_features, non_specific_features, and no_occurrence.

Details

Features are categorized into specific, non-specific, and no-occurrence groups based on Gini thresholds and optional binarization of EWCSR values.

See also

ewcsr.sparse, gini.rank.fs

Examples

if (FALSE) { # \dontrun{
fs <- gini.ewcsr.fs(mat)
} # }