#' @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)

}