discretize_exprs_supervised: supervised_disc_df

In FCBF: Fast Correlation Based Filter for Feature Selection

Description

Uses several discretizations and selects the one that is best for a given variable (gene) in comparison to a target class by equivocation

Usage

discretize_exprs_supervised(expression_table, target, parallel = FALSE)

Arguments

expression_table	A previously normalized expression table
target	A series of labels matching each of the values in the gene vector (genes in rows, cells/samples in columns)
parallel	Set calculations in parallel. May be worth it if the number of rows and columns is really large. Do watchout for memory overload.

Value

A data frame with the discretized features in the same order as previously

Examples

data(scDengue)
exprs <- as.data.frame(SummarizedExperiment::assay(scDengue, 'logcounts'))
exprs <- exprs [1:200, 1:120]
infection <- SummarizedExperiment::colData(scDengue)
target <- infection$infection
discrete_expression <- as.data.frame(discretize_exprs_supervised(exprs,target))
fcbf(discrete_expression,target, thresh = 0.05, verbose = TRUE)

FCBF documentation built on Nov. 8, 2020, 8:30 p.m.