combinatorial_phenotype_counts: Count cells for each phenotype for each sample

In SciOmicsLab/PhenoComb: Phenotype Combinatorial Analysis

Count cells for each phenotype for each sample

Description

combinatorial_phenotype_counts generates phenotypes considering all possible combination of markers and count the number of cells for each phenotype for each sample.

Usage

combinatorial_phenotype_counts(
  processed_cell_data,
  parent_phen = NULL,
  min_count = 10,
  sample_fraction_min_counts = 0,
  max_phenotype_length = 0,
  efficient = FALSE,
  n_threads = 1
)

Arguments

processed_cell_data	Data.Frame containing filtered and thresholded cell data. Use function process_cell_data to generate this input.
parent_phen	Parent phenotype to filter for. All phenotypes generated will contain the parent phenotype.
min_count	Minimum number of cells that a phenotype must have for at least one sample.
sample_fraction_min_counts	Fraction of samples that must have at least min_count cells (value between 0 ~ 1). Value forced to minimum of 1/n_samples.
max_phenotype_length	Maximum length of markers to compose a phenotype.
efficient	If TRUE, filter full-length phenotypes for min_count condition before generating all marker combinations. It is less sensitive for very rare phenotypes but yields a great boost in performance.
n_threads	Number of threads to be used. Default: 1.

Value

Data.Frame with all possible phenotypes and cell counts for each sample.

SciOmicsLab/PhenoComb documentation built on Aug. 26, 2023, 1:28 p.m.