discretize {fcoex} | R Documentation

## Set the discretized expression attribute Uses the discretize_exprs function of the FCBF package

### Description

Set the discretized expression attribute Uses the discretize_exprs function of the FCBF package

### Usage

    discretize(
      fc,
      number_of_bins = 4,
      method = "varying_width",
      min_max_cutoff = 0.25
    )

    ## S4 method for signature 'fcoex'
    discretize(
      fc,
      number_of_bins = 4,
      method = "varying_width",
      min_max_cutoff = 0.25
    )

### Arguments

`fc` | Object of class `fcoex`
`number_of_bins` | Number of equal-width bins for discretization. Note: it is a binary discretization, with the first bin becoming one class ('low') and the other bins, another class ('high'). Defaults to 4.
`method` | Method applied to all genes for discretization. Methods available: "varying_width" (Binarization modulated by the number_of_bins param), "mean" (Split in ON/OFF by each gene mean expression), "median" (Split in ON/OFF by each gene median expression), "min_max_%" (Similat to the "varying width", a binarization threshold in a % of the min-max range is set. (minmax% param)),
`min_max_cutoff` | <- Modulator for the "min_max_%" method. Defaults to 0.25.

### Value

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

### Examples

    library(SingleCellExperiment)
    data("mini_pbmc3k")
    targets <- colData(mini_pbmc3k)$clusters
    exprs <- as.data.frame(assay(mini_pbmc3k, "logcounts"))
    fc <- new_fcoex(exprs, targets)
    fc <- discretize(fc)

[Package fcoex version 1.6.0 Index]