R/do_PathwayActivityPlot.R

In SCpubr: Generate Publication Ready Visualizations of Single Cell Transcriptomics Data

#' Plot Pathway Activities from decoupleR using Progeny prior knowledge.
#'
#' @inheritParams doc_function
#' @param activities \strong{\code{\link[tibble]{tibble}}} | Result of running decoupleR method with progeny regulon prior knowledge.
#'
#' @return A ggplot2 object.
#' @export
#'
#' @example /man/examples/examples_do_PathwayActivityPlot.R

do_PathwayActivityPlot <- function(sample,
                                   activities,
                                   group.by = NULL,
                                   split.by = NULL,
                                   slot = "scale.data",
                                   statistic = "norm_wmean",
                                   pt.size = 1,
                                   border.size = 2,
                                   na.value = "grey75",
                                   legend.position = "bottom",
                                   legend.width = 1,
                                   legend.length = 20,
                                   legend.framewidth = 0.5,
                                   legend.tickwidth = 0.5,
                                   legend.framecolor = "grey50",
                                   legend.tickcolor = "white",
                                   legend.type = "colorbar",
                                   font.size = 14,
                                   font.type = "sans",
                                   axis.text.x.angle = 45,
                                   enforce_symmetry = TRUE,
                                   min.cutoff = NA,
                                   max.cutoff = NA,
                                   number.breaks = 5,
                                   diverging.palette = "RdBu",
                                   diverging.direction = -1,
                                   use_viridis = FALSE,
                                   viridis.palette = "G",
                                   viridis.direction = -1,
                                   sequential.palette = "YlGnBu",
                                   sequential.direction = 1,
                                   flip = FALSE,
                                   return_object = FALSE,
                                   grid.color = "white",
                                   border.color = "black",
                                   plot.title.face = "bold",
                                   plot.subtitle.face = "plain",
                                   plot.caption.face = "italic",
                                   axis.title.face = "bold",
                                   axis.text.face = "plain",
                                   legend.title.face = "bold",
                                   legend.text.face = "plain"){
  # Add lengthy error messages.
  withr::local_options(.new = list("warning.length" = 8170))


  check_suggests(function_name = "do_PathwayActivityPlot")
  # Check if the sample provided is a Seurat object.
  check_Seurat(sample = sample)

  # Check logical parameters.
  logical_list <- list("enforce_symmetry" = enforce_symmetry,
                       "flip" = flip,
                       "return_object" = return_object,
                       "use_viridis" = use_viridis)
  check_type(parameters = logical_list, required_type = "logical", test_function = is.logical)
  # Check numeric parameters.
  numeric_list <- list("pt.size" = pt.size,
                       "border.size" = border.size,
                       "font.size" = font.size,
                       "legend.width" = legend.width,
                       "legend.length" = legend.length,
                       "legend.framewidth" = legend.framewidth,
                       "legend.tickwidth" = legend.tickwidth,
                       "axis.text.x.angle" = axis.text.x.angle,
                       "min.cutoff" = min.cutoff,
                       "max.cutoff" = max.cutoff,
                       "number.breaks" = number.breaks,
                       "viridis.direction" = viridis.direction,
                       "sequential.direction" = sequential.direction,
                       "diverging.direction" = diverging.direction)
  check_type(parameters = numeric_list, required_type = "numeric", test_function = is.numeric)
  # Check character parameters.
  character_list <- list("group.by" = group.by,
                         "slot" = slot,
                         "split.by" = split.by,
                         "na.value" = na.value,
                         "legend.position" = legend.position,
                         "legend.framecolor" = legend.framecolor,
                         "font.type" = font.type,
                         "legend.tickcolor" = legend.tickcolor,
                         "legend.type" = legend.type,
                         "diverging.palette" = diverging.palette,
                         "viridis.palette" = viridis.palette,
                         "sequential.palette" = sequential.palette,
                         "statistic" = statistic,
                         "grid.color" = grid.color,
                         "border.color" = border.color,
                         "plot.title.face" = plot.title.face,
                         "plot.subtitle.face" = plot.subtitle.face,
                         "plot.caption.face" = plot.caption.face,
                         "axis.title.face" = axis.title.face,
                         "axis.text.face" = axis.text.face,
                         "legend.title.face" = legend.title.face,
                         "legend.text.face" = legend.text.face)
  check_type(parameters = character_list, required_type = "character", test_function = is.character)

  check_colors(legend.framecolor, parameter_name = "legend.framecolor")
  check_colors(legend.tickcolor, parameter_name = "legend.tickcolor")
  check_colors(na.value, parameter_name = "na.value")
  check_colors(grid.color, parameter_name = "grid.color")
  check_colors(border.color, parameter_name = "border.color")

  check_parameters(parameter = font.type, parameter_name = "font.type")
  check_parameters(parameter = legend.type, parameter_name = "legend.type")
  check_parameters(parameter = axis.text.x.angle, parameter_name = "axis.text.x.angle")
  check_parameters(parameter = number.breaks, parameter_name = "number.breaks")
  check_parameters(parameter = diverging.palette, parameter_name = "diverging.palette")
  check_parameters(plot.title.face, parameter_name = "plot.title.face")
  check_parameters(plot.subtitle.face, parameter_name = "plot.subtitle.face")
  check_parameters(plot.caption.face, parameter_name = "plot.caption.face")
  check_parameters(axis.title.face, parameter_name = "axis.title.face")
  check_parameters(axis.text.face, parameter_name = "axis.text.face")
  check_parameters(legend.title.face, parameter_name = "legend.title.face")
  check_parameters(legend.text.face, parameter_name = "legend.text.face")
  check_parameters(viridis.direction, parameter_name = "viridis.direction")
  check_parameters(sequential.direction, parameter_name = "sequential.direction")
  check_parameters(diverging.direction, parameter_name = "diverging.direction")

  `%>%` <- magrittr::`%>%`

  # Generate the continuous color palette.
  if (isTRUE(enforce_symmetry)){
    colors.gradient <- compute_continuous_palette(name = diverging.palette,
                                                  use_viridis = FALSE,
                                                  direction = diverging.direction,
                                                  enforce_symmetry = enforce_symmetry)
  } else {
    colors.gradient <- compute_continuous_palette(name = ifelse(isTRUE(use_viridis), viridis.palette, sequential.palette),
                                                  use_viridis = use_viridis,
                                                  direction = ifelse(isTRUE(use_viridis), viridis.direction, sequential.direction),
                                                  enforce_symmetry = enforce_symmetry)
  }

  sample[["progeny"]] <- activities %>%
                         dplyr::filter(.data$statistic == .env$statistic) %>%
                         tidyr::pivot_wider(id_cols = "source",
                                            names_from = "condition",
                                            values_from = "score") %>%
                         tibble::column_to_rownames("source") %>%
                         Seurat::CreateAssayObject()

  Seurat::DefaultAssay(sample) <- "progeny"
  sample@assays$progeny@key <- "progeny_"

  # Scale the data.
  sample <- Seurat::ScaleData(sample, verbose = FALSE)

  list.out <- list()

  if (!is.null(split.by) & !is.null(group.by)){
    assertthat::assert_that(length(group.by) == 1,
                            msg = paste0(add_cross(), crayon_body("When using "),
                                         crayon_key("split.by"),
                                         crayon_body(" make sure you only provide a single value to "),
                                         crayon_key("group.by"),
                                         crayon_body(". Otherwise, the prot will not keep the proportions. This is a design choice. Thanks!")))
  }


  if (is.null(group.by)) {
    sample$Groups <- Seurat::Idents(sample)
    sample$group.by <- sample$Groups
    group.by <- "Groups"
  }
  # Plotting
  list.out <- list()

  matrix.list <- list()
  for (group in group.by){
    # Extract activities from object as a long dataframe
    suppressMessages({
      sample$group.by <- sample@meta.data[, group]
      
      suppressWarnings({
      df <- t(as.matrix(SeuratObject::GetAssayData(object = sample,
                                      assay = "progeny",
                                      slot = slot))) %>%
            as.data.frame() %>%
            tibble::rownames_to_column(var = "cell") %>%
            dplyr::left_join(y = {sample@meta.data[, "group.by", drop = FALSE] %>%
                                  tibble::rownames_to_column(var = "cell")},
                                  by = "cell") %>%
            dplyr::select(-"cell") %>%
            tidyr::pivot_longer(cols = -"group.by",
                                names_to = "source",
                                values_to = "score") %>%
            dplyr::group_by(.data$group.by, .data$source) %>%
            dplyr::summarise(mean = mean(.data$score, na.rm = TRUE))
      })
      df.order <- df
      df.order[is.na(df.order)] <- 0

      matrix.list[[group]][["df"]] <- df
      matrix.list[[group]][["df.order"]] <- df.order


      if (!is.null(split.by)){
        sample$split.by <- sample@meta.data[, split.by]
        suppressWarnings({
        df.split <- t(as.matrix(SeuratObject::GetAssayData(object = sample,
                                              assay = "progeny",
                                              slot = slot))) %>%
                    as.data.frame() %>%
                    tibble::rownames_to_column(var = "cell") %>%
                    dplyr::left_join(y = {sample@meta.data[, c("group.by", "split.by"), drop = FALSE] %>%
                                          tibble::rownames_to_column(var = "cell")},
                                          by = "cell") %>%
                    dplyr::select(-"cell") %>%
                    tidyr::pivot_longer(cols = -c("group.by", "split.by"),
                                        names_to = "source",
                                        values_to = "score") %>%
                    dplyr::group_by(.data$split.by, .data$group.by, .data$source) %>%
                    dplyr::summarise(mean = mean(.data$score, na.rm = TRUE))
        matrix.list[[group]][["df.split"]] <- df.split
        })
      }
    })
  }


  counter <- 0
  for (group in group.by){
    counter <- counter + 1

    df <- matrix.list[[group]][["df"]]
    df.order <- matrix.list[[group]][["df.order"]]

    data <- df

    if (!is.null(split.by)){
      data <- matrix.list[[group]][["df.split"]]
    }

    # Transform to wide to retrieve the hclust.
    df.order <- df.order %>%
                tidyr::pivot_wider(id_cols = "group.by",
                                   names_from = 'source',
                                   values_from = 'mean') %>%
                tibble::column_to_rownames("group.by") %>%
                as.matrix()
    if(length(rownames(df.order)) == 1){
      row_order <- rownames(df.order)[1]
    } else {
      row_order <- rownames(df.order)[stats::hclust(stats::dist(df.order, method = "euclidean"), method = "ward.D")$order]
    }
    if (counter == 1){
      # nocov start
      if (length(colnames(df.order)) == 1){
        col_order <- colnames(df.order)[1]
      # nocov end
      } else {
        col_order <- colnames(df.order)[stats::hclust(stats::dist(t(df.order), method = "euclidean"), method = "ward.D")$order]
      }
    }

    data <- data %>%
            dplyr::mutate("source" = factor(.data$source, levels = rev(col_order)),
                          "group.by" = factor(.data$group.by, levels = row_order))
    matrix.list[[group]][["data.mean"]] <- data
    if (!is.na(min.cutoff)){
      data <- data %>%
              dplyr::mutate("mean" = ifelse(.data$mean < min.cutoff, min.cutoff, .data$mean))
    }

    if (!is.na(max.cutoff)){
      data <- data %>%
              dplyr::mutate("mean" = ifelse(.data$mean > max.cutoff, max.cutoff, .data$mean))
    }

    matrix.list[[group]][["data"]] <- data
  }

  # Compute limits.
  min.vector <- NULL
  max.vector <- NULL

  for (group in group.by){
    data <- matrix.list[[group]][["data.mean"]]

    min.vector <- append(min.vector, min(data$mean, na.rm = TRUE))
    max.vector <- append(max.vector, max(data$mean, na.rm = TRUE))
  }

  # Get the absolute limits of the datasets.
  limits <- c(min(min.vector),
              max(max.vector))

  # Compute overarching scales for all heatmaps.
  scale.setup <- compute_scales(sample = sample,
                                feature = " ",
                                assay = "progeny",
                                reduction = NULL,
                                slot = slot,
                                number.breaks = number.breaks,
                                min.cutoff = min.cutoff,
                                max.cutoff = max.cutoff,
                                flavor = "Seurat",
                                enforce_symmetry = enforce_symmetry,
                                from_data = TRUE,
                                limits.use = limits)


  # Plot individual heatmaps.
  counter <- 0
  list.heatmaps <- list()
  for (group in group.by){
    counter <- counter + 1
    data <- matrix.list[[group]][["data"]]

    p <- data %>%
         # nocov start
         ggplot2::ggplot(mapping = ggplot2::aes(x = if(base::isFALSE(flip)){.data$source} else {.data$group.by},
                                                y = if(base::isFALSE(flip)){.data$group.by} else {.data$source},
                                                fill = .data$mean)) +
         # nocov end
         ggplot2::geom_tile(color = grid.color, linewidth = 0.5) +
         ggplot2::scale_y_discrete(expand = c(0, 0)) +
         ggplot2::scale_x_discrete(expand = c(0, 0),
                                   position = "top") +
         ggplot2::guides(y.sec = guide_axis_label_trans(~paste0(levels(.data$group.by))),
                         x.sec = guide_axis_label_trans(~paste0(levels(.data$source)))) +
         ggplot2::coord_equal() +
         ggplot2::scale_fill_gradientn(colors = colors.gradient,
                                       na.value = na.value,
                                       name = paste0("Pathway score | ", statistic, ifelse(slot == "scale.data", " | Scaled + Centered", "")),
                                       breaks = scale.setup$breaks,
                                       labels = scale.setup$labels,
                                       limits = scale.setup$limits)

    if (!is.null(split.by)){
      p <- p +
           ggplot2::facet_grid(~ .data$split.by,
                               drop = FALSE)
    }

    p <- modify_continuous_legend(p = p,
                                  legend.title = paste0("Pathway score | ", statistic),
                                  legend.aes = "fill",
                                  legend.type = legend.type,
                                  legend.position = legend.position,
                                  legend.length = legend.length,
                                  legend.width = legend.width,
                                  legend.framecolor = legend.framecolor,
                                  legend.tickcolor = legend.tickcolor,
                                  legend.framewidth = legend.framewidth,
                                  legend.tickwidth = legend.tickwidth)
    # nocov start
    # Set axis titles.
    if (base::isFALSE(flip)){
      if (counter == 1){
        if (length(group.by) > 1){
          xlab <- NULL
        } else {
          xlab <- "Pathway"
        }

        ylab <- group
      } else {
        if (length(group.by) > 1){
          if (counter == length(group.by)){
            xlab <- "Pathway"
          } else {
            xlab <- NULL
          }
        } else {
          xlab <- NULL
        }
        ylab <- group
      }
    } else {
      if (counter == 1){
        ylab <- "Pathway"

        xlab <- group
      } else {
        ylab <- NULL
        xlab <- group
      }
    }
    # nocov end


    axis.parameters <- handle_axis(flip = flip,
                                   group.by = group.by,
                                   group = group,
                                   counter = counter,
                                   axis.text.x.angle = axis.text.x.angle,
                                   plot.title.face = plot.title.face,
                                   plot.subtitle.face = plot.subtitle.face,
                                   plot.caption.face = plot.caption.face,
                                   axis.title.face = axis.title.face,
                                   axis.text.face = axis.text.face,
                                   legend.title.face = legend.title.face,
                                   legend.text.face = legend.text.face)

    # Set theme
    p <- p +
         ggplot2::xlab(xlab) +
         ggplot2::ylab(ylab) +
         ggplot2::theme_minimal(base_size = font.size) +
         ggplot2::theme(axis.ticks.x.bottom = axis.parameters$axis.ticks.x.bottom,
                        axis.ticks.x.top = axis.parameters$axis.ticks.x.top,
                        axis.ticks.y.left = axis.parameters$axis.ticks.y.left,
                        axis.ticks.y.right = axis.parameters$axis.ticks.y.right,
                        axis.text.y.left = axis.parameters$axis.text.y.left,
                        axis.text.y.right = axis.parameters$axis.text.y.right,
                        axis.text.x.top = axis.parameters$axis.text.x.top,
                        axis.text.x.bottom = axis.parameters$axis.text.x.bottom,
                        axis.title.x.bottom = axis.parameters$axis.title.x.bottom,
                        axis.title.x.top = axis.parameters$axis.title.x.top,
                        axis.title.y.right = axis.parameters$axis.title.y.right,
                        axis.title.y.left = axis.parameters$axis.title.y.left,
                        strip.background = axis.parameters$strip.background,
                        strip.clip = axis.parameters$strip.clip,
                        strip.text = axis.parameters$strip.text,
                        legend.position = if (is.null(split.by)) {legend.position} else {"bottom"},
                        axis.line = ggplot2::element_blank(),
                        plot.title = ggplot2::element_text(face = plot.title.face, hjust = 0),
                        plot.subtitle = ggplot2::element_text(face = plot.subtitle.face, hjust = 0),
                        plot.caption = ggplot2::element_text(face = plot.caption.face, hjust = 1),
                        legend.text = ggplot2::element_text(face = legend.text.face),
                        legend.title = ggplot2::element_text(face = legend.title.face),
                        plot.title.position = "plot",
                        panel.grid = ggplot2::element_blank(),
                        panel.grid.minor.y = ggplot2::element_line(color = "white", linewidth = 1),
                        text = ggplot2::element_text(family = font.type),
                        plot.caption.position = "plot",
                        legend.justification = "center",
                        plot.margin = ggplot2::margin(t = 0, r = 10, b = 0, l = 10),
                        panel.border = ggplot2::element_rect(fill = NA, color = border.color, linewidth = 1),
                        panel.grid.major = ggplot2::element_blank(),
                        plot.background = ggplot2::element_rect(fill = "white", color = "white"),
                        panel.background = ggplot2::element_rect(fill = "white", color = "white"),
                        legend.background = ggplot2::element_rect(fill = "white", color = "white"))

    list.heatmaps[[group]] <- p
  }

  # Plot the combined plot
  input <- if(base::isFALSE(flip)){list.heatmaps[rev(group.by)]}else{list.heatmaps[group.by]}
  p <- patchwork::wrap_plots(input,
                             ncol = if (base::isFALSE(flip)){1} else {NULL},
                             nrow = if(isTRUE(flip)) {1} else {NULL},
                             guides = "collect")
  p <- p +
    patchwork::plot_annotation(theme = ggplot2::theme(legend.position = legend.position,
                                                      plot.title = ggplot2::element_text(family = font.type,
                                                                                         color = "black",
                                                                                         face = plot.title.face,
                                                                                         hjust = 0),
                                                      plot.subtitle = ggplot2::element_text(family = font.type,
                                                                                            face = plot.subtitle.face,
                                                                                            color = "black",
                                                                                            hjust = 0),
                                                      plot.caption = ggplot2::element_text(color = "black",
                                                                                           face = plot.caption.face,
                                                                                           hjust = 1,
                                                                                           family = font.type),
                                                      plot.caption.position = "plot"))

  list.out[["Heatmap"]] <- p

  if (isTRUE(return_object)){
    list.out[["Object"]] <- sample
    return_me <- list.out
  } else{
    return_me <- list.out[["Heatmap"]]
  }

  return(return_me)
}