R/plot_bar_composition.R

In nicohuttmann/pOmics: Framework for proteomics data analysis

#' Plots data as bar plot with ggplot2
#'
#' @param data_ data_
#' @param TERMS TERMS to plot
#' @param type type of data to represent ("Fraction" or "Count")
#' @param color names vector of colors
#' @param xlab labels of x-axis
#' @param ylab label of y-axis
#' @param legend.name name of legend
#' @param legend.position position of legend ("none", "right", "bottom",
#' "top", "left")
#' @param aspect.ratio aspect ratio of x- and y-axis
#' @param custom.theme predefined theme for plot
#' @param ... arguments for custom.theme
#' @param view view plot after generation
#' @param input name of input data
#' @param output name of output data
#'
#' @return
#' @export
#'
#' @import ggplot2
#'
plot_bar_composition <- function(data_,
                                 TERMS = "mitochondrion",
                                 type = "Fraction",
                                 color,
                                 xlab = "Fraction of Proteins",
                                 ylab = "",
                                 legend.name = "",
                                 legend.position = "right",
                                 aspect.ratio = 1,
                                 custom.theme = theme_phosprot_half_open,
                                 ...,
                                 view = T,
                                 input = "data_annotation_composition",
                                 output = "plot_annotation_composition") {

  # Handle input
  input_list <- data_input(data_ = data_, input = input)

  if (input_list[["error"]]) return(invisible(input_list[["data"]]))

  else {
    data <- input_list[["data"]]
    input <- input_list[["input"]] # Remove if not used

  }


  data.melt_1 <- data %>%
    dplyr::filter(TERM %in% TERMS) %>%
    dplyr::select(c(TERM, starts_with("count"))) %>%
    reshape2::melt() %>%
    dplyr::mutate(variable = gsub("count.", "", variable))

  data.melt_2 <- data %>%
    dplyr::filter(TERM %in% TERMS) %>%
    dplyr::select(c(starts_with("percent"))) %>%
    reshape2::melt() %>%
    dplyr::mutate(variable = gsub("percent.", "", variable))

  #data.melt <- dplyr::full_join(data.melt_1, data.melt_2, "variable")
  data.melt <- cbind(data.melt_1, dplyr::select(data.melt_2, -variable))

  names(data.melt) <- c("TERM", "variable", "Count", "Fraction")

  # Change names of annotations
  if (length(names(TERMS)) > 0) {

    names(TERMS)[names(TERMS) == ""] <- TERMS[names(TERMS) == ""]

    data.melt$TERM <- names(TERMS)[match(data.melt$TERM, TERMS)]

  }


  data.melt$variable <- factor(data.melt$variable,
                               levels = rev(unique(data.melt$variable)))
  data.melt$TERM <- factor(data.melt$TERM,
                           levels = rev(unique(data.melt$TERM)))


  if (!hasArg(color))
    color <- rev(RColorBrewer::brewer.pal(9, "Blues")[c(3,5,7)])

  # Plot
  p <- ggplot(data = data.melt, aes(x = TERM,
                                    y = .data[[type]],
                                    fill = variable)) +
    geom_bar(stat = "identity", position = "dodge") +
    scale_fill_manual(name = legend.name,
                      values = color,
                      guide = guide_legend(reverse=TRUE)) +
    custom.theme(...) +
    theme(axis.text.x = element_text(angle = 0, hjust = 0.5),
          axis.text.y = element_text(vjust = 0.5),
          aspect.ratio = aspect.ratio,
          legend.position = legend.position) +
    coord_flip() +
    xlab(ylab) +
    ylab(xlab)

  if (type == "Fraction") {
    p <- p +
      scale_y_continuous(labels = scales::percent)
  }



  # Print plot
  if (view) print(p)



  # Prepare return
  if (input_list[["list.input"]]) data_[[output]] <- p

  else data_ <- p

  # Return
  return(invisible(data_))
}