discretize_exprs_supervised {FCBF} | R Documentation

## supervised_disc_df

### 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, minimum_su = 0.05, verbose = TRUE)

[Package FCBF version 2.2.0 Index]