R/dplot_across_osns.R

In ropensci/DoOR.functions: Integrating Heterogeneous Odorant Response Data into a Common Response Model: A DoOR to the Complete Olfactome

#' dplot_across_osns
#'
#' plot the activation patterns of one or several odorants across OSNs
#'
#' @param odorants character vector, one or several InChIKeys
#' @param response_matrix DOOR response matrix, contains the data to plot
#' @param odor_data data frame, contains the odorant information.
#' @param zero character, InChIKey of the odorant that should be set to 0 (e.g.
#'   SFR)
#' @param tag character, the chemical identifier to use in the plot, one of
#'   \code{colnames(odor)}
#' @param plot.type interger, 1 or 2, defining the type of plot (1: facet_grid
#'   of odorants * sensillae, 2: facet_wrap across OSNs)
#' @param base_size numeric, the base font size for the ggplot2 plot
#' @param sub character vector, specify one or several classes of sensilla the
#'   plot should be restricted to. One or several of: "ab" "ac", "at", "ai",
#'   "pb", "sacI", "sacII"
#' @param door_mappings data frame, containing the mappings of response profiles
#'   to morphological structures.
#'
#' @details DoOR response profiles will be selected and ordered according to the
#'   OSNs they are related to. Several DoOR response profiles might exist for a
#'   given OSN (e.g. one for the OSN itself and one for the OSNs misexpressed
#'   receptor protein) but only one will be shown. Which DoOR profile is mapped
#'   to which OSN is controlled via the "code.OSN" column in \code{DoORmapings}.
#'
#' @return a ggplot2 object
#' @aliases dplot_acrossOSNs dplot_across_osns
#' @export
#'
#' @examples
#' # load DoOR data & functions
#' library(DoOR.data)
#' library(DoOR.functions)
#' 
#' # pick example odorants by name ans transform their ID to InChIKey 
#' odorants <- trans_id(c("1-butanol", "isopentyl acetate", "carbon dioxide", "water"), 
#' from = "Name", to = "InChIKey")
#'  
#' # plot                                      
#' dplot_across_osns(odorants)
#' # plot only across ac and at sensillae
#' dplot_across_osns(odorants, sub = c("ac", "at"))
#' # plot across sensory neurons
#' dplot_across_osns(odorants, plot.type = 2)
#' @author Daniel Münch <\email{daniel.muench@@uni-konstanz.de}>
dplot_across_osns <- function(odorants,
                  response_matrix = door_default_values("door_response_matrix"),
                  odor_data = door_default_values("odor"),
                  door_mappings = door_default_values("door_mappings"),
                  zero = door_default_values("zero"),
                  tag  = "Name",
                  sub,
                  plot.type = 1,
                  base_size = 12) {
  if (!requireNamespace("ggplot2", quietly = TRUE))
    stop(
      "ggplot2 is required for plotting, please install via 
       install.packages('ggplot2')",
      call. = FALSE
    )
  
  if (!is.null(zero))
    response_matrix <-
      as.data.frame(apply(response_matrix, 2, function(x)
        reset_sfr(x, x[zero])))
  
  odorants <- as.character(odorants)
  
  data <- response_matrix[odorants, ]
  data <- door_melt(as.data.frame(data), na.rm = FALSE)
  
  if (tag != "InChIKey")
    data$odorant <-
    odor_data[match(data$odorant, odor_data$InChIKey), tag]
  
  data$sensillum <-
    door_mappings[match(data$dataset, door_mappings$receptor), "sensillum"]
  data$OSN       <-
    door_mappings[match(data$dataset, door_mappings$receptor), "code.OSN"]
  data           <- subset(data, sensillum != "")
  data$OSN       <-
    gsub("ab|ac|at|ai|pb|sacI|sacII|[0-9]", "", data$OSN)
  data           <- subset(data,!is.na(OSN))
  data$group     <-
    paste(data$sensillum, data$OSN, " (", data$dataset, ")", sep = "")
  
  
  # resort sensillum levels (ab9 and ab10)
  w9 <- which(levels(data$sensillum) == "ab9")
  w10 <- which(levels(data$sensillum) == "ab10")
  data$sensillum <-
    factor(data$sensillum, levels = levels(data$sensillum)[c(1:(w10 - 1), (w10 +
           1):(w9 - 1), w9, w10, (w9 + 1):length(levels(data$sensillum)))])
  
  # resort group levels (the fast, less failsave way)
  data$group <- factor(data$group)
  data$group <-
    factor(data$group, levels = levels(data$group)[c(3:21, 1:2, 
                                                22:length(levels(data$group)))])
  
  if (!missing(sub))
    data <-
    data[grep(paste0("^", sub, collapse = "|"), data$sensillum), ]
  
  if (plot.type == 1) {
    plot <-
      ggplot2::ggplot(data, ggplot2::aes(
        x = OSN,
        y = value,
        fill = OSN,
        color = OSN
      )) +
      ggplot2::geom_bar(stat = "identity",
                        position = "identity",
                        alpha = .6) +
      ggplot2::facet_grid(odorant ~ sensillum) +
      ggplot2::theme_minimal(base_size = base_size) +
      ggplot2::theme(
        panel.border  = ggplot2::element_rect(fill = NA, color = "grey"),
        axis.ticks.x  = ggplot2::element_blank(),
        axis.text.x   = ggplot2::element_blank(),
        axis.title.x  = ggplot2::element_blank()
      ) +
      ggplot2::geom_text(
        ggplot2::aes(label = dataset),
        angle = -90,
        size = .3 * base_size,
        y = -.02,
        alpha = .9,
        hjust = 0
      )
  }
  
  if (plot.type == 2) {
    plot <-
      ggplot2::ggplot(data,
                      ggplot2::aes(
                        x = odorant,
                        y = value,
                        fill = odorant,
                        color = odorant
                      )) +
      ggplot2::geom_bar(stat = "identity",
                        position = "identity",
                        alpha = .6) +
      ggplot2::facet_wrap( ~ group) +
      ggplot2::theme_minimal(base_size = base_size) +
      ggplot2::theme(
        panel.border = ggplot2::element_rect(fill = NA, color = "grey"),
        axis.ticks.x = ggplot2::element_blank(),
        axis.text.x  = ggplot2::element_blank(),
        axis.title.x = ggplot2::element_blank()
      )
  }
  
  return(plot)
  
}