R/RpartDT.R

In DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

#' @title RPART Decision Tree
#' @description The decision tree analysis is implemented over a training
#'   dataset, which consisted of the DEGs obtained by either SAMseq or the
#'   binomial differential expression.
#' @param data The exact output of the exprmclust function.
#' @param quiet If `TRUE`, suppresses intermediary output
#' @param plot If `FALSE`, suppresses plot output
#' @export
#' @importFrom rpart rpart
#' @importFrom rpart.plot rpart.plot
#' @return Information about the model and, by default, a plot of the decision
#'   tree.
RpartDT <- function(data, quiet = FALSE, plot = TRUE) {
  exp.df <- as.data.frame(t(data))
  exp.df$classVector <- factor(colnames(data))
  model <- rpart(
    classVector ~ .,
    exp.df,
    method = "class",
    minsplit = 1,
    cp = -1
  )
  if (!quiet) print(model)
  if (plot) rpart.plot(model, type = 4, extra = 101)
  return(model)
}