compute_positivity_many: Compute positivity of multiple phenotypes

In akoyabio/phenoptrReports: Create reports using Phenoptics data

Description

Compute positivity of multiple phenotypes

Usage

compute_positivity_many(
  csd,
  phenotypes,
  positivity_pairs,
  tissue_categories = NULL
)

Arguments

csd	Cell seg data to use. This should already have been filtered for the slides or fields of interest.
phenotypes	A named list of phenotype selectors (see phenoptr::parse_phenotypes).
positivity_pairs	A named list of pairs (lists) of phenotype names and positivity expressions. The expressions must be one-sided formulas such as ~`Membrane PDL1 (Opal 520) Mean`>pdl1_threshold.
tissue_categories	Optional vector of tissue category names to include.

Value

A data frame with columns for count, positive count, and percent for each element of positivity_pairs.

See Also

Other aggregation functions: compute_density_from_cell_summary(), compute_density_from_table(), compute_h_score_from_score_data(), compute_h_score(), compute_mean_expression_many(), compute_mean_expression(), compute_positivity(), count_phenotypes(), counts_to_percents()

akoyabio/phenoptrReports documentation built on Jan. 17, 2022, 6:22 p.m.