Plotting of numbers of significantly regulated reactions in metabolic subsystems. The plot() method for actiData objects.

Author: PiotrTymoszuk

NAMESPACE

@@ -5,6 +5,7 @@ S3method(count_regulated,actiData)
 S3method(get_activity,data.frame)
 S3method(get_activity,matrix)
 S3method(identify_regulated,actiData)
+S3method(plot,actiData)
 S3method(print,actiData)
 S3method(print,reactDB)
 S3method(select,actiData)
@@ -20,8 +21,10 @@ export(get_regulation)
 export(identify_regulated)
 export(is_actiData)
 export(is_reactDB)
+export(plot.actiData)
 export(plot_errors)
 export(plot_mc)
+export(plot_numbers)
 export(reactDB)
 export(select.actiData)
 export(transform_estimates)
@@ -44,6 +47,7 @@ importFrom(furrr,future_map)
 importFrom(future,plan)
 importFrom(generics,components)
 importFrom(ggplot2,aes)
+importFrom(ggplot2,geom_bar)
 importFrom(ggplot2,geom_hline)
 importFrom(ggplot2,geom_line)
 importFrom(ggplot2,geom_point)
@@ -54,6 +58,8 @@ importFrom(ggplot2,ggplot)
 importFrom(ggplot2,is.theme)
 importFrom(ggplot2,labs)
 importFrom(ggplot2,position_jitter)
+importFrom(ggplot2,scale_fill_manual)
+importFrom(ggplot2,scale_x_continuous)
 importFrom(microViz,theme_micro)
 importFrom(purrr,compact)
 importFrom(purrr,map)

R/actiData_methods.R

@@ -428,4 +428,63 @@
 
   }
 
+# Plotting -----------
+
+#' Diagnostic plots and visualization of reaction activity in `actiData` objects.
+#'
+#' @description
+#' Diagnostic plots and visualization of estimates of regulation of reaction
+#' activity - the plotting method for \code{\link{actiData}} objects.
+#'
+#' @details
+#' The `plot()` method for \code{\link{actiData}} objects generates the following
+#' types of plots specified by `plot_type` argument:
+#'
+#' * `plot_type = "errors"`: scatter plot of regulation estimates and their errors
+#' made with \code{\link{plot_errors}}.
+#'
+#' * `plot_type = "numbers"`: bar/stack plots of numbers or percentages of
+#' differentially regulated
+#' reactions in subsystems generated with \code{\link{plot_numbers}}. Please note
+#' that the regulation status of metabolic reactions in `x` has to be determined
+#' prior to plotting by calling \code{\link{identify_regulated}}.
+#'
+#' * `plot_type == "mc"`: plots of reactions regulation estimates in single
+#' iterations of the Monte Carlo simulation with \code{\link{plot_mc}}.
+#'
+#' @return a `ggplot` graphic object.
+#'
+#' @param x an \code{\link{actiData}} object.
+#' @param plot_type plot type, see Details.
+#' @param ... additional arguments passed to the plotting functions specified
+#' in Details.
+#'
+#' @seealso [get_regulation()]
+#'
+#' @md
+#'
+#' @export plot.actiData
+#' @export
+
+  plot.actiData <- function(x,
+                            plot_type = c("errors",
+                                          "numbers",
+                                          "mc"), ...) {
+
+    ## input control --------
+
+    stopifnot(is_actiData(x))
+
+    plot_type <- match.arg(plot_type[1],
+                           c("errors", "numbers", "mc"))
+
+    ## re-routing ----------
+
+    switch(plot_type,
+           errors = plot_errors(x, ...),
+           numbers = plot_numbers(x, ...),
+           mc = plot_mc(x, ...))
+
+  }
+
 # END ---------

R/imports.R

@@ -39,7 +39,9 @@
 #' @importFrom ggplot2 geom_violin
 #' @importFrom ggplot2 geom_vline
 #' @importFrom ggplot2 geom_hline
-#'
+#' @importFrom ggplot2 geom_bar
+#' @importFrom ggplot2 scale_fill_manual
+#' @importFrom ggplot2 scale_x_continuous
 #' @importFrom ggplot2 position_jitter
 #' @importFrom ggplot2 is.theme
 #' @importFrom ggplot2 labs

R/plotting_funs.R

@@ -385,4 +385,182 @@
 
   }
 
+# Plotting of numbers of significantly regulate reactions ---------
+
+#' Bar/stack plots with numbers of significantly activated and inhibited reactions.
+#'
+#' @description
+#' Representation of numbers or percentages of differentially regulated
+#' reactions in subsystems as bar or stack plot.
+#'
+#' @details
+#' Please make sure that the object contains activity regulation status
+#' information.
+#' If not, please call \code{\link{identify_regulated}} prior to
+#' counting the significant effects.
+#'
+#' The plot type is determined by `type` argument:
+#' `"plus_minus"` (bar plot, inhibited reaction as "negative" numbers),
+#' `"bar"` (bar plot, dodged bars for inhibited and activated reactions),
+#' `"stack"` plot.
+#'
+#' @return a `ggplot` graphic.
+#'
+#' @inheritParams plot_errors
+#' @param scale type of the frequency statistic to be shown in the plot:
+#' count (default) or percentage of reactions in the subsystem.
+#' @param type type of the plot, see Details.
+#' @param show_all logical, should frequencies of all regulated reactions be
+#' presented in the plot together with counts/percentages for the subsystems?
+#' @param palette color palette: a named character vector with at least two elements
+#' specifying the colors for activated and inhibited reactions.
+#' @param bar_rim_color color of the bar's rim/line.
+#' @param show_n_total logical: if `TRUE`, total numbers of reactions in subsystems
+#' are displayed in the Y axis along with the subsystem names.
+#' @param labeller_fun a function used to transform subsystem names, e.g. into
+#' abbreviations, which are shown in the Y axis of the plot.
+#' @param fill_lab title of the fill scale.
+#' @param ... additional arguments passed to \code{\link[ggplot2]{geom_bar}}.
+#'
+#' @export
+
+  plot_numbers <- function(x,
+                           reactions = NULL,
+                           subsystems = NULL,
+                           scale = c("count", "percent"),
+                           type = c("plus_minus", "bar", "stack"),
+                           palette = c("activated" = "firebrick",
+                                       "inhibited" = "steelblue"),
+                           bar_rim_color = "black",
+                           show_all = FALSE,
+                           labeller_fun = identity,
+                           show_n_total = TRUE,
+                           cust_theme = microViz::theme_micro(),
+                           plot_title = NULL,
+                           plot_subtitle = NULL,
+                           x_lab = NULL,
+                           y_lab = "subsystem",
+                           fill_lab = "regulation\nstatus", ...) {
+
+    ## input control --------
+
+    if(!is_actiData(x)) stop("`x` has to be an `actiData` object.", call. = FALSE)
+
+    scale <- match.arg(scale[1], c("count", "percent"))
+
+    type <- match.arg(type[1], c("plus_minus", "bar", "stack"))
+
+    stopifnot(is.logical(show_all))
+    show_all <- show_all[1]
+
+    stopifnot(is.logical(show_n_total))
+    show_n_total <- show_n_total[1]
+
+    stopifnot(is.character(palette))
+
+    if(length(palette) < 2) {
+
+      stop("`palette` has to have at least two color names.", call. = FALSE)
+
+    }
+
+    palette <- palette[1:2]
+
+    if(!is_function(labeller_fun)) {
+
+      stop("`labeller_fun` has to be a function.", call = FALSE)
+
+    }
+
+    if(!is.null(cust_theme)) {
+
+      if(!is.theme(cust_theme)) {
+
+        stop("`cust_theme` has to be a `ggplot` theme object.", call. = FALSE)
+
+      }
+
+    }
+
+    ## plotting data --------
+
+    x <- select(x, reactions, subsystems)
+
+    count_data <- count_regulated(x)
+
+    if(!show_all) {
+
+      count_data <- filter(count_data, .data[["subsystem"]] != "all")
+
+    }
+
+    plot_variable <- switch(scale,
+                            count = "n",
+                            percent = "percent")
+
+    count_data[["axis_label"]] <- labeller_fun(count_data[["subsystem"]])
+
+    if(show_n_total) {
+
+      count_data[["axis_label"]] <-
+        paste(count_data[["axis_label"]],
+              count_data[["n_total"]],
+              sep = "\nn = ")
+
+    }
+
+    if(is.null(x_lab)) {
+
+      x_lab <- switch(scale,
+                      count = "number of reactions",
+                      percent = "% of subsystem reactions")
+
+    }
+
+    ## the plots ----------
+
+    if(type %in% c("bar", "stack")) {
+
+      pos_txt <- switch(type,
+                        bar = "dodge",
+                        stack = "stack")
+
+      number_plot <- ggplot(count_data,
+                            aes(x = .data[[plot_variable]],
+                                y = reorder(.data[["axis_label"]],
+                                            .data[[plot_variable]]),
+                                fill = .data[["regulation"]])) +
+        geom_bar(stat = "identity",
+                 color = bar_rim_color,
+                 position = pos_txt, ...)
+
+    } else {
+
+      number_plot <- ggplot(count_data,
+                            aes(x = ifelse(.data[["regulation"]] == "activated",
+                                           .data[[plot_variable]],
+                                           -.data[[plot_variable]]),
+                                y = reorder(.data[["axis_label"]],
+                                            .data[[plot_variable]]),
+                                fill = .data[["regulation"]])) +
+        geom_bar(stat = "identity",
+                 color = bar_rim_color, ...) +
+        scale_x_continuous(labels = abs)
+
+    }
+
+    if(!is.null(cust_theme)) number_plot <- number_plot + cust_theme
+
+    number_plot +
+      geom_vline(xintercept = 0) +
+      scale_fill_manual(values = palette,
+                        drop = FALSE) +
+      labs(title = plot_title,
+           subtitle = plot_subtitle,
+           x = x_lab,
+           y = y_lab,
+           fill = fill_lab)
+
+  }
+
 # END --------

inst/examples/development.R

@@ -155,28 +155,47 @@
 # Diagnostic plots ----------
 
   tst_norm_estimates %>%
-    plot_errors(fun = log2,
-                line_color = "orangered3",
-                fill = "gray80")
+    plot(plot_type = "errors",
+         fun = log2,
+         line_color = "orangered3",
+         fill = "gray80")
 
   tst_mc_estimates %>%
-    plot_errors(subsystems = "Fatty acid oxidation",
-                fun = sqrt,
-                line_color = "orangered3",
-                line_alpha = 0.5,
-                fill = "gray80")
+    plot(plot_type = "errors",
+         subsystems = "Fatty acid oxidation",
+         fun = sqrt,
+         line_color = "orangered3",
+         line_alpha = 0.5,
+         fill = "gray80")
 
   tst_norm_estimates %>% plot_mc
 
   tst_mc_estimates %>%
-    plot_mc(subsystems = "Oxidative phosphorylation",
-            fun = sqrt)
+    plot(plot_type = "mc",
+         subsystems = "Oxidative phosphorylation",
+         fun = sqrt)
 
   tst_mc_estimates %>%
-    plot_mc(subsystems = "Oxidative phosphorylation",
-            fun = sqrt,
-            type = "violin",
-            point_alpha = 0.15,
-            plot_title = "Oxidative phosphorylation")
+    plot(plot_type = "mc",
+         subsystems = "Oxidative phosphorylation",
+         fun = sqrt,
+         type = "violin",
+         point_alpha = 0.15,
+         plot_title = "Oxidative phosphorylation")
+
+  tst_mc_estimates %>%
+    identify_regulated %>%
+    plot(plot_type = "numbers",
+         scale = "percent",
+         type = "plus_minus",
+         subsystems = c("Oxidative phosphorylation",
+                        "Citric acid cycle",
+                        "Glycolysis/gluconeogenesis",
+                        "Fatty acid synthesis",
+                        "Fatty acid oxidation"),
+         plot_title = "Energy metabolism")
+
+# Subsystem enrichment ---------
+
 
 # END --------