compute_AUC: Compute Area Under Curve for a matrix of samples

In cgplab/ROCkerMeth: Receiver Operating Characteristic curves analyzer for DNA methylation data

Compute Area Under Curve for a matrix of samples

Description

This function computes the Area Under Curve used to define the segregation between tumor and control samples accordingly to their methylation (beta) values.

Usage

compute_AUC(
  tumor_table,
  control_table,
  ncores = 1,
  na_threshold,
  return_info = FALSE,
  min_samples_frac = 1
)

Arguments

tumor_table	A matrix of beta-values (percentage) from tumor samples.
control_table	A matrix of beta-values (percentage) from normal/control samples.
ncores	Number of parallel processes to use for parallel computing.
na_threshold	(DEPRECATED) Fraction of NAs (considered independently in tumor and control samples) above which a site will not be selected (default=0).
return_info	If TRUE (default) return a vector else compute all AUC and return a data.frame reporting fraction of NAs in tumor and control tables.
min_samples_frac	Fraction of samples (independently in tumor and control samples) that are not NA required to analyze a site (range=0-1, default=1).

Value

A vector of AUC scores (NA if not analyzed) or a data.frame with AUC scores and the fraction of non-NA samples in tumor and contol tables.

Examples

auc_data <- compute_AUC(tumor_toy_table, control_toy_table)

cgplab/ROCkerMeth documentation built on March 27, 2022, 9:57 p.m.