R/mitochondrialPercentage-plot.R

In seriph78/COTAN: COexpression Tables ANalysis

#' @details `mitochondrialPercentagePlot()` plots the raw library size for each
#'   cell and sample.
#'
#' @param objCOTAN a `COTAN` object
#' @param genePrefix Prefix for the mitochondrial genes (default "^MT-" for
#'   Human, mouse "^mt-")
#' @param condName The name of a condition in the `COTAN` object to further
#'   separate the cells in more sub-groups. When no condition is given it is
#'   assumed to be the same for all cells (no further sub-divisions)
#' @param conditions The *conditions* to use. If given it will take precedence
#'   on the one indicated by `condName` that will only indicate the relevant
#'   column name in the returned `data.frame`

#'
#' @importFrom ggplot2 ggplot
#' @importFrom ggplot2 geom_point
#' @importFrom ggplot2 position_jitter
#' @importFrom ggplot2 geom_boxplot
#' @importFrom ggplot2 labs
#' @importFrom ggplot2 scale_y_continuous
#' @importFrom ggplot2 ylim
#'
#' @importFrom Matrix rowSums
#'
#' @importFrom rlang is_empty
#'
#' @importFrom stringr str_detect
#'
#' @returns `mitochondrialPercentagePlot()` returns a `list` with:
#'   * `"plot"` a `violin-boxplot` object
#'   * `"sizes"` a sizes `data.frame`
#'
#' @export
#'
#' @examples
#' mitPercPlot <-
#'   mitochondrialPercentagePlot(objCOTAN, genePrefix = "g-0000")[["plot"]]
#' plot(mitPercPlot)
#'
#' @rdname RawDataCleaning
#'
mitochondrialPercentagePlot <- function(objCOTAN, genePrefix = "^MT-",
                                        condName = "", conditions = NULL) {
  sizes <- getCellsSize(objCOTAN)
  sizes <- as.data.frame(sizes)

  sizes <- setColumnInDF(sizes, seq_len(nrow(sizes)), colName = "n")

  c(., conditions) %<-%
    normalizeNameAndLabels(objCOTAN, name = condName,
                           labels = conditions, isCond = TRUE)
  assert_that(!is_empty(conditions))

  sizes <- setColumnInDF(sizes, conditions[rownames(sizes)], colName = "sample")

  mitGenes <- getGenes(objCOTAN)[str_detect(getGenes(objCOTAN),
                                            pattern = genePrefix)]
  if (is_empty(mitGenes)) {
    stop("gene prefix resulted in no matches")
  }

  mitGenesData <-
    getRawData(objCOTAN)[getGenes(objCOTAN) %in% mitGenes, , drop = FALSE]
  if (!identical(colnames(mitGenesData), rownames(sizes))) {
    warning("Problem with cells' order!")
  }
  mitGenesData <- t(mitGenesData)
  sizes <- setColumnInDF(sizes, rowSums(mitGenesData), colName = "sum.mit")
  sizes <- setColumnInDF(sizes, colName = "mit.percentage",
                         colToSet = round(100.0 * sizes[["sum.mit"]] /
                                            sizes[["sizes"]], digits = 2L))

  plot <-
    sizes %>%
    ggplot(aes(x = sample, y = mit.percentage, fill = sample)) +
    #geom_point(size = 0.5) +
    geom_flat_violin(position = position_nudge(x = 0.15, y = 0.0),
                     adjust = 2.0, alpha = 0.5) +
    geom_point(position = position_jitter(width = 0.1),
               size = 0.4, color = "black", alpha = 0.5) +
    geom_boxplot(aes(x = sample, y = mit.percentage, fill = sample),
                 outlier.shape = NA, alpha = 0.8,
                 width = 0.15, colour = "gray65", size = 0.6) +
    labs(title = "Mitochondrial percentage of reads",
         y = "% (mit. reads / tot reads * 100)",
         x = "") +
    scale_y_continuous(expand = c(0.0, 0.0)) +
    #ylim(0L, max(sizes[["sizes"]])) +
    plotTheme("size-plot")

  return(list("plot" = plot, "sizes" = sizes))
}