R/PLOT-bubble_ko.R

In mirnavazquez/RbiMs: R Tools for Reconstruncting Bin Metabolisms

#' @title Bubble plot of KO/Pathways/Modules and its relative abundance 
#' within each bin.
#' @description Creates a bubble plot of KO/Pathways/Modules relative 
#' abundance within each bin. 
#' It uses the metadata information to color bubbles.
#' @usage bubble_ko(tibble_ko, x_axis, y_axis, calc=NULL, 
#' data_experiment=NULL, color_character=NULL, order_bins=NULL,
#' order_metabolism=NULL, color_pallet=NULL, range_size=NULL, 
#' x_labs=TRUE, y_labs=TRUE, text_x=NULL, text_y=NULL)
#' @param tibble_ko a tibble object, created with the mapping_ko 
#' get_subset_* functions or with importing functions. 
#' @param x_axis a string, a column name of the metabolism table. 
#' It determined the x axis label.
#' @param y_axis a string, a column name of the metabolism table. 
#' It determined the y axis label.
#' @param calc a character indicating with type of calc should 
#' be done to plot the results. Valid values are "Abundance", "Binary", 
#' "Percentage", and "None". If you chose none you are expected to use a
#' tibble table obtained from calc_binary or calc_percentage. 
#' @param data_experiment optional. a data frame object 
#' containing metadata information.
#' @param color_character optional. a string column name of the metadata 
#' or metabolism object, used for color.
#' @param order_bins optional. a character vector indicating the bin order.
#' @param order_metabolism optional. a character vector 
#' indicating metabolism order.
#' @param color_pallet optional. a character vector of colors to use.
#' @param range_size optional. a numeric vector indicating 
#' the range size of the dots.
#' @param x_labs optional. If FALSE it will set the x lab to NULL. 
#' @param y_labs optional. If FALSE it will set the y lab to NULL. 
#' @param text_x optional. A numeric vector indicating the size
#'  of the x text letters.
#' @param text_y optional. A numeric vector indicating the size
#'  of the y text letters.
#' @details This function is part of a package used for 
#' the calc of bins metabolism.
#' @import ggplot2 dplyr rlang pals
#' @examples
#' \dontrun{
#' bubble_ko(ko_bin_mapp, Bin_name, Module, "Binary", metadata, Clades)
#' }
#' @noRd
bubble_ko<-function(tibble_ko,
                    x_axis, 
                    y_axis,
                    calc=NULL,
                    data_experiment=NULL,
                    color_character=NULL,
                    order_bins=NULL,
                    order_metabolism=NULL,
                    color_pallet=NULL, 
                    range_size=NULL,
                    x_labs=TRUE,
                    y_labs=TRUE,
                    text_x=NULL,
                    text_y=NULL){
  # Enquoting -------------------------------------------------------------####
  x_axis_enquo <- enquo(x_axis)
  y_axis_enquo <- enquo(y_axis)
  x_axis_label <- as_label(x_axis_enquo)
  y_axis_label <- as_label(y_axis_enquo)
  color_character_enquo <- enquo(color_character)
  # Checking axis ---------------------------------------------------------####
  if( x_axis_label  != "Bin_name") {
    y_axis_enquo<-enquo(x_axis) 
    x_axis_enquo<-enquo(y_axis)
    x_axis_label<-as_label(x_axis_enquo)
    y_axis_label<-as_label(y_axis_enquo)
  } 
  # Checking the color ----------------------------------------------------####
  if(is.null(color_pallet) == T){
    color_pallet<-as.vector(cols25(20))
    warning("if your vector is >25, choose another color pallet. Make sure you 
            are renaming your variables correctly.")
  }
  # Checking the size -----------------------------------------------------####
  if(is.null(range_size) == T){
    range_size<-c(1,5)
  }
  # Checking the xlabs ----------------------------------------------------####
  if(isTRUE(x_labs) == T){
    x_labs<-x_axis_enquo
  } else if (isTRUE(x_labs) == F) {
    x_labs<-NULL
  }
  # Checking the ylabs ----------------------------------------------------####
  if(isTRUE(y_labs) == T){
    y_labs<-y_axis_enquo
  } else if (isTRUE(y_labs) == F) {
    y_labs<-NULL
  }
  # Checking the text_x ----------------------------------------------------####
  if(is.null(text_x) == T){
    text_x<-7
  }
  # Checking the text_x ----------------------------------------------------####
  if(is.null(text_y) == T){
    text_y<-7
  }
  # Check calc --------------------------------------------------------####
  if(is.null(calc) == T){
    calc<-NULL
  }
  if(calc == "Abundance"){
    tibble_ko_mod<-calc_binary(tibble_ko, !!y_axis_enquo, binary=FALSE) %>%
      rename(tmp = .data$Abundance)
  } else if (calc == "Binary") {
    tibble_ko_mod<-calc_binary(tibble_ko, !!y_axis_enquo) %>%
      rename(tmp = .data$Presence_absence)
  } else if (calc == "Percentage") {
    tibble_ko_mod<-calc_percentage(tibble_ko, !!y_axis_enquo) %>%
      rename(tmp = .data$Percentage)
  } else if (calc == "None") {
    if( "Presence_absence" %in% colnames(tibble_ko)){
      tibble_ko_mod <-rename(tibble_ko, tmp = .data$Presence_absence)
    } else if ( "Abundance" %in% colnames(tibble_ko)){
      tibble_ko_mod <-rename(tibble_ko, tmp = .data$Abundance)
    } else if ( "Percentage" %in% colnames(tibble_ko)){
      tibble_ko_mod <-rename(tibble_ko, tmp = .data$Percentage)
    }
  }
  # Transform integer ----------------------------------------------------####
  Table_with_percentage<-tibble_ko_mod %>%
    select({{y_axis_enquo}}, .data$Bin_name, .data$tmp) %>%
    drop_na() %>%
    distinct()  %>%
    mutate_at("tmp", as.integer) %>%
    mutate(tmp = case_when(
      .data$tmp == 0 ~ NA_integer_,
      TRUE ~ as.integer(.data$tmp)
    )) 
  # Join data experiment --------------------------------------------------####
  if(is.null(data_experiment) == F){
    Table_with_percentage<-Table_with_percentage %>%
      left_join(data_experiment, by="Bin_name")
  }
  # Checking the order ---------------------------------------------------####
  if(is.null(order_metabolism) == T){
    order_metabolism<-Table_with_percentage %>%
      ungroup() %>%
      select({{y_axis_enquo}}) %>%
      distinct() %>%
      pull()
  }
  # Checking the order ---------------------------------------------------####
  if(is.null(order_bins) == T){
    order_bins<-sort(unique(Table_with_percentage$Bin_name))
  }
  # Checking experiment ---------------------------------------------------####
  if(is.null(data_experiment) == T){
    data_experiment <- NULL
  }
  # Normal / upside -------------------------------------------------------####
  rm(x_axis_enquo, y_axis_enquo, x_axis_label, y_axis_label)
  x_axis_enquo <- enquo(x_axis)
  y_axis_enquo <- enquo(y_axis)
  x_axis_label <- as_label(x_axis_enquo)
  y_axis_label <- as_label(y_axis_enquo)
  # Plot ------------------------------------------------------------------####
  if(x_axis_label == "Bin_name") {
    plot_bubble<-ggplot(Table_with_percentage,
                        aes(x= factor(!!x_axis_enquo, 
                                      levels = !!order_bins),
                            y= factor(!!y_axis_enquo, 
                                      levels = !!order_metabolism),
                            size= .data$tmp,
                            color= !!color_character_enquo)) +
      geom_point(alpha=0.5) +
      scale_size(range =range_size) +
      scale_color_manual(values = color_pallet) +
      theme_linedraw() +
      theme(axis.text.x = element_text(size=text_x, 
                                       angle = 45, 
                                       hjust = 1, 
                                       vjust = 1),
            axis.text.y = element_text(size=text_y))+
      xlab(x_labs) + 
      ylab(y_axis_enquo)
  } else if (x_axis_label != "Bin_name" ) {
    plot_bubble<-ggplot(Table_with_percentage,
                        aes(x= factor(!!x_axis_enquo, 
                                      levels = !!order_metabolism),
                            y= factor(!!y_axis_enquo, 
                                      levels = !!order_bins),
                            size= .data$tmp,
                            color= !!color_character_enquo)) +
      geom_point(alpha=0.5) +
      scale_size(range = c(1,5)) +
      scale_color_manual(values = color_pallet) +
      theme_linedraw() +
      theme(axis.text.x = element_text(size=text_x, 
                                       angle = 45, 
                                       hjust = 1, 
                                       vjust = 1),
            axis.text.y = element_text(size=text_y))+
      xlab(x_labs) + 
      ylab(y_labs)
    
  }
  
  # Check calc plot --------------------------------------------------------####
  if(calc == "Abundance"){
    Table_with_percentage<-Table_with_percentage %>%
      rename(Abundance = .data$tmp)
    plot_bubble <- suppressMessages(plot_bubble + guides(size=guide_legend(title="Abundance")))
  } else if (calc == "Binary") {
    Table_with_percentage<-Table_with_percentage %>%
      rename("Presence/Absence" = .data$tmp)
    plot_bubble <- suppressMessages(plot_bubble + scale_size_continuous(name="", labels = "Present"))
  } else if (calc == "Percentage") {
    Table_with_percentage<-Table_with_percentage %>%
      rename(Percentage = .data$tmp)
    plot_bubble <- suppressMessages(plot_bubble + guides(size=guide_legend(title="Percentage")))
  } else if (calc == "None") {
    plot_bubble<- plot_bubble
    }
  suppressWarnings(return(plot_bubble))
}