categorical_labeling: categorical_labelling

In matei-ionita/Tailor: Gaussian mixture modeling for heavy-tailed distributions in Flow Cytometry data

Description

If major phenotype definitions are available (e.g. "CD4 Naive"), based on only a few of the markers in the panel, label each categorical cluster by one of these major phenotypes.

Usage

categorical_labeling(tailor_obj, defs)

Arguments

tailor_obj	A tailor object, as obtained from tailor.learn.
defs	A matrix or data frame giving definitions of major phenotypes.

Value

The tailor object, with updated information about categorical labels.

Examples

fileName <- system.file("extdata", "sampled_flowset_old.rda",
                        package = "Tailor")
load(fileName)
tailor_params <- flowCore::colnames(fs_old)[c(7:9, 11:22)]
tailor_obj <- tailor_learn(data = fs_old,
                          params = tailor_params,
                          mixture_components = 50)

defs <- read.csv("~/git/R/packages/Tailor/inst/extdata/pheno_definitions.csv",
                 row.names = 1, stringsAsFactors = FALSE)
tailor_obj <- categorical_labeling(tailor_obj, defs)

matei-ionita/Tailor documentation built on Jan. 4, 2021, 11:47 a.m.