R/outcome2factor.r

In ggpmisc: Miscellaneous Extensions to 'ggplot2'

#' Convert numeric ternary outcomes into a factor
#'
#' @param x a numeric vector of -1, 0, and +1 values, indicating down-regulation,
#'   uncertain response or up-regulation, or a numeric vector that can be
#'   converted into such values using a pair of thresholds.
#' @param n.levels numeric Number of levels to create, either 3 or 2.
#' @param threshold numeric vector Range enclosing the values to be considered
#'   uncertain.
#'
#' @details These functions convert the numerically encoded values into a factor
#'   with the three levels \code{"down"}, \code{"uncertain"} and \code{"up"}, or
#'   into a factor with two levels \code{de} and \code{uncertain} as expected by
#'   default by scales \code{\link{scale_colour_outcome}},
#'   \code{\link{scale_fill_outcome}} and \code{\link{scale_shape_outcome}}.
#'   When \code{n.levels = 2} both -1 and +1 are merged to the same level of the
#'   factor with label \code{"de"}.
#'
#' @note These are convenience functions that only save some typing. The same
#'   result can be achieved by a direct call to \code{\link{factor}} and
#'   comparisons. These functions aim at making it easier to draw volcano and
#'   quadrant plots.
#'
#' @family Functions for quadrant and volcano plots
#'
#' @export
#'
#' @examples
#'
#' outcome2factor(c(-1, 1, 0, 1))
#' outcome2factor(c(-1, 1, 0, 1), n.levels = 2L)
#'
#' threshold2factor(c(-0.1, -2, 0, +5))
#' threshold2factor(c(-0.1, -2, 0, +5), n.levels = 2L)
#' threshold2factor(c(-0.1, -2, 0, +5), threshold = c(-1, 1))
#'
#' @family scales for omics data
#'
outcome2factor <- function(x, n.levels = 3L) {
  stopifnot(all(unique(stats::na.omit(x)) %in% -1:1))
  if (n.levels == 3L) {
    fct.labels <- c( "up", "uncertain","down")
  } else if (n.levels == 2) {
    fct.labels <- c("de", "uncertain", "de")
  }
  factor(x, levels = c(+1, 0, -1), labels = fct.labels)
}

#' @rdname outcome2factor
#'
#' @export
#'
threshold2factor <- function(x, n.levels = 3L, threshold = 0) {
  threshold <- range(threshold)
  z <- ifelse(x < threshold[1], -1,
              ifelse(x > threshold[2], 1,
                     0))
  outcome2factor(z, n.levels = n.levels)
}

#' Convert two numeric ternary outcomes into a factor
#'
#' @param x,y numeric vectors of -1, 0, and +1 values, indicating down
#'   regulation, uncertain response or up-regulation, or numeric vectors that can be
#'   converted into such values using a pair of thresholds.
#' @param x_threshold,y_threshold numeric vector Ranges enclosing the values to be considered
#'   uncertain for each of the two vectors..
#'
#' @details This function converts the numerically encoded values into a factor
#'   with the four levels \code{"xy"}, \code{"x"}, \code{"y"} and \code{"none"}.
#'   The factor created can be used for faceting or can be mapped to aesthetics.
#'
#' @note This is an utility function that only saves some typing. The same
#'   result can be achieved by a direct call to \code{\link{factor}}. This
#'   function aims at making it easier to draw quadrant plots with facets
#'   based on the combined outcomes.
#'
#' @family Functions for quadrant and volcano plots
#'
#' @export
#'
#' @examples
#'
#' xy_outcomes2factor(c(-1, 0, 0, 1, -1), c(0, 1, 0, 1, -1))
#' xy_thresholds2factor(c(-1, 0, 0, 1, -1), c(0, 1, 0, 1, -1))
#' xy_thresholds2factor(c(-1, 0, 0, 0.1, -5), c(0, 2, 0, 1, -1))
#'
#' @family scales for omics data
#'
xy_outcomes2factor <- function(x, y) {
  stopifnot(all(unique(stats::na.omit(x)) %in% -1:1) &&
              all(unique(stats::na.omit(y)) %in% -1:1))
  stopifnot(length(x) == length(y))
  factor(
    ifelse(x & y, "xy",
           ifelse(x, "x",
                  ifelse(y, "y", "none"))),
    levels = c("xy", "x", "y", "none")
  )
}

#' @rdname xy_outcomes2factor
#'
#' @export
#'
xy_thresholds2factor <- function(x, y,
                                 x_threshold = 0,
                                 y_threshold = 0) {
  x_threshold <- range(x_threshold)
  xx <- ifelse(x < x_threshold[1], -1,
              ifelse(x > x_threshold[2], 1,
                     0))
  y_threshold <- range(y_threshold)
  yy <- ifelse(y < y_threshold[1], -1,
               ifelse(y > y_threshold[2], 1,
                      0))
  xy_outcomes2factor(xx, yy)
}