R/BoxScatter_Plot.R

In davidrequena/drfun: Functions To Help With RNAseq Data Analysis

############################
# Function BoxScatter_Plot #
############################

#' Function to make Box-Scatter plots.
#'
#' This function will make a Boxplot, using a DEseq object.
#' It will show the data points on top with a small deviation (jitter) for a better visualization.
#'
#' @param object A DEseq object already transformed with the variance stabilizing or rlog transformations.
#' @param variables To indicate the variables to be used as Shape and Fill of the markers.
#' @param genename The gene name to be used for the plot.
#' @param symbol The gene symbol to be used for the plot.
#' @param labels A vector containing the x-labels of the box-plot. Default: c("N", "P", "R", "M").
#' @param categories A vector containing the labels for the legend. Default: c("normal", "primary", "recurrence", "metastasis").
#' @param colors Vector of colors to be used for the categories of the variable assigned as Marker Fill.
#' @param shapes Vector of shapes to be used for the categories of the variable assigned as Marker Shape.
#' @param markersize Size of the marker.
#' @param alpha Transparency of the marker, which goes from 0 (transparent) to 1 (no transparent). Default: 0.8.
#' @param width Width of the plot.
#' @param height Height of the plot.
#' @param jitter Random deviation added to the dots. Default: 0.2.
#' @param dpi DPI of the plot. Default: 150.
#' @param save To save the plot. Default: FALSE.
#' @param title_size Font of the title and axis names. Default: c(axis = 20, fig = 24).
#' @param label_size Font of the labels (x-axis) and numbers (y-axis). Default: c(x = 20, y = 16).
#' @param legend_size Font of the title and elements of the legend. Default: c(title = 14, elements = 12).
#' @export

BoxScatter_Plot <- function (object = NULL, variables = c(fill = "VarFill", shape = "VarShape"),
                             genename = NULL, symbol = NULL, labels = c("N", "P", "R", "M"),
                             categories = c("normal", "primary", "recurrence", "metastasis"),
                             colors = NULL, shapes = NULL, markersize = NULL, alpha = 0.8,
                             width = NULL, height = NULL, jitter = 0.2, dpi = 150, save = FALSE,
                             title_size = c(axis = 20, fig = 24), label_size = c(x = 20, y = 16),
                             legend_size = c(title = 14, elements = 12)) {
  
  require("DESeq2")
  
  # Extracting the vector of counts for that gene
  gene_counts <- counts(object, normalized = TRUE)[genename, ]
  log2_gc <- log2(gene_counts)

  # Making a dataframe for the plot
  df.box <- data.frame(object@colData[, c("id", "sample_type", variables)], log2_gc)

  # Re-ordering sample_type for the plot
  df.box$sample_type <- factor(df.box$sample_type,
                               levels = categories,
                               labels = labels)

  # Plot
  p.bs <- ggplot(df.box, aes(x = sample_type, y = log2_gc)) +
    theme_bw() + geom_boxplot(width = 0.6, fill = "gray90") +
    labs(title = paste("Gene:", genename, symbol),
         x = expression("Sample Type"),
         y = expression("log"[2]*"(Normalized Gene Counts)")) +
    theme(plot.title = element_text(size = title_size["fig"]),
          axis.title = element_text(size = title_size["axis"]),
          axis.text.x = element_text(size = label_size["x"]),
          axis.text.y = element_text(size = label_size["y"]),
          legend.title = element_text(size = legend_size["title"]),
          legend.text=element_text(size = legend_size["elements"]))

  if (length(variables) == 1) {
    p.bs <- p.bs + geom_point(data = df.box, aes_string(fill = variables["fill"]), shape = 21,
                              size = markersize, alpha = alpha, color = "black",
                              position = position_jitter(width = jitter))

  } else if (length(variables) == 2) {
    p.bs <- p.bs + geom_point(data = df.box, aes_string(fill = variables["fill"], shape = variables["shape"]),
                              size = markersize, alpha = alpha, color = "black",
                              position = position_jitter(width = jitter)) +
      scale_shape_manual(name = variables["shape"], values = shapes)

  } else { return("Up to two variables allowed") }

  p.bs <- p.bs + scale_fill_manual(name = variables[1], values = colors,
                                   guide = guide_legend(override.aes = aes(shape = 21, size = 7)))

  if (save == T) {
    ggsave(paste0(symbol,".jpg"), plot = p.bs, width = width, height = height, dpi = dpi)

  } else { return(p.bs) }
}