discretize_gene_supervised {FCBF}R Documentation

discretize_gene_supervised

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_gene_supervised(gene, target, output = "discretized_vector",
  discs = c(".split_vector_in_two_by_median",
  ".split_vector_in_two_by_mean", ".split_vector_by_kmeans",
  ".split_vector_in_three_by_mean_sd", ".split_vector_in_two_by_vw"),
  vw_params = c(0.25, 0.5, 0.75), kmeans_centers = c(2, 3, 4),
  sd_alpha = c(0.75, 1, 1.25))

Arguments

gene

A previously normalized gene expression vector

target

A series of labels matching each of the values in the gene vector

output

If it is equal to 'discretized_vector', the output is the vector. I it is 'su', returns a dataframe. Defaults to 'discretized_vector'

discs

Defaults to c( ".split_vector_in_two_by_median", split_vector_in_two_by_mean", ".split_vector_by_kmeans", ".split_vector_in_three_by_mean_sd", ".split_vector_in_two_by_vw")

vw_params

cuttof parameters for the varying width function. Defaults to 0.25, 0.5 and 0.75

kmeans_centers

Numeric vector with the number of centers to use for kmeans. Defaults to 2, 3 and 4

sd_alpha

Parameter for adusting the 'medium' level of the mean +- sd discretization. Defaults to sd_alpha = c(0.75, 1, 1.25))

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'))
gene <- exprs['ENSG00000166825',]
infection <- SummarizedExperiment::colData(scDengue)
target <- infection$infection
discrete_expression <- as.data.frame(discretize_gene_supervised(gene, target))
table(discrete_expression)

[Package FCBF version 1.2.1 Index]