Nothing
R/do_DimPlot.R
In SCpubr: Generate Publication Ready Visualizations of Single Cell Transcriptomics Data
Defines functions
do_DimPlot
Documented in
do_DimPlot
#' Wrapper for \link[Seurat]{DimPlot}.
#'
#' @inheritParams doc_function
#' @param idents.keep \strong{\code{\link[base]{character}}} | Vector of identities to keep. This will effectively set the rest of the cells that do not match the identities provided to NA, therefore coloring them according to na.value parameter.
#' @param shuffle \strong{\code{\link[base]{logical}}} | Whether to shuffle the cells or not, so that they are not plotted cluster-wise. Recommended.
#' @param order \strong{\code{\link[base]{character}}} | Vector of identities to be plotted. Either one with all identities or just some, which will be plotted last.
#' @param sizes.highlight \strong{\code{\link[base]{numeric}}} | Point size of highlighted cells using cells.highlight parameter.
#' @return A ggplot2 object containing a DimPlot.
#' @export
#'
#' @example man/examples/examples_do_DimPlot.R
do_DimPlot <- function(sample,
reduction = NULL,
group.by = NULL,
split.by = NULL,
colors.use = NULL,
shuffle = TRUE,
order = NULL,
raster = FALSE,
pt.size = 1,
label = FALSE,
label.color = "black",
label.fill = "white",
label.size = 4,
label.box = TRUE,
repel = FALSE,
cells.highlight = NULL,
idents.highlight = NULL,
idents.keep = NULL,
sizes.highlight = 1,
ncol = NULL,
plot.title = NULL,
plot.subtitle = NULL,
plot.caption = NULL,
legend.title = NULL,
legend.position = "bottom",
legend.title.position = "top",
legend.ncol = NULL,
legend.nrow = NULL,
legend.icon.size = 4,
legend.byrow = FALSE,
raster.dpi = 2048,
dims = c(1, 2),
font.size = 14,
font.type = "sans",
na.value = "grey75",
plot_cell_borders = TRUE,
border.size = 2,
border.color = "black",
border.density = 1,
plot_marginal_distributions = FALSE,
marginal.type = "density",
marginal.size = 5,
marginal.group = TRUE,
plot.axes = FALSE,
plot_density_contour = FALSE,
contour.position = "bottom",
contour.color = "grey90",
contour.lineend = "butt",
contour.linejoin = "round",
contour_expand_axes = 0.25,
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_DimPlot")
# Check if the sample provided is a Seurat object.
check_Seurat(sample = sample)
sample <- check_Assay5(sample)
# Check the reduction.
reduction <- check_and_set_reduction(sample = sample, reduction = reduction)
# Check the dimensions.
dims <- check_and_set_dimensions(sample = sample, reduction = reduction, dims = dims)
# Check logical parameters.
logical_list <- list("label" = label,
"repel" = repel,
"shuffle" = shuffle,
"legend.byrow" = legend.byrow,
"raster" = raster,
"plot_marginal_distributions" = plot_marginal_distributions,
"marginal.group" = marginal.group,
"plot_cell_borders" = plot_cell_borders,
"plot.axes" = plot.axes,
"plot_density_contour" = plot_density_contour,
"label.box" = label.box)
check_type(parameters = logical_list, required_type = "logical", test_function = is.logical)
# Check numeric parameters.
numeric_list <- list("pt.size" = pt.size,
"sizes.highlight" = sizes.highlight,
"legend.ncol" = legend.ncol,
"legend.nrow" = legend.nrow,
"font.size" = font.size,
"legend.icon.size" = legend.icon.size,
"ncol" = ncol,
"raster.dpi" = raster.dpi,
"marginal.size" = marginal.size,
"border.size" = border.size,
"contour_expand_axes" = contour_expand_axes,
"label.size" = label.size,
"border.density" = border.density)
check_type(parameters = numeric_list, required_type = "numeric", test_function = is.numeric)
# Check character parameters.
character_list <- list("legend.position" = legend.position,
"plot.title" = plot.title,
"plot.subtitle" = plot.subtitle,
"plot.caption" = plot.caption,
"legend.title" = legend.title,
"cells.highlight" = cells.highlight,
"idents.keep" = idents.keep,
"order" = order,
"na.value" = na.value,
"idents.highlight" = idents.highlight,
"legend.title.position" = legend.title.position,
"font.type" = font.type,
"marginal.type" = marginal.type,
"border.color" = border.color,
"contour.position" = contour.position,
"contour.color" = contour.color,
"contour.lineend" = contour.lineend,
"contour.linejoin" = contour.linejoin,
"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)
# Checks to ensure proper function.
group_by_and_split_by_used <- !(is.null(split.by)) & !(is.null(group.by))
group_by_and_highlighting_cells <- (!(is.null(cells.highlight)) | !(is.null(idents.highlight))) & !(is.null(group.by))
split_by_and_highlighting_cells <- (!(is.null(cells.highlight)) | !(is.null(idents.highlight))) & !(is.null(split.by))
order_and_shuffle_used <- !(is.null(order)) & isTRUE(shuffle)
assertthat::assert_that(!group_by_and_highlighting_cells,
msg = paste0(add_cross(), crayon_body("Either "),
crayon_key("group.by"),
crayon_body(" or "),
crayon_key("cells.highlight | idents.hightlight"),
crayon_body(" have to be set to "),
crayon_key("NULL"),
crayon_body(".")))
assertthat::assert_that(!split_by_and_highlighting_cells,
msg = paste0(add_cross(), crayon_body("Either "),
crayon_key("split.by"),
crayon_body(" or "),
crayon_key("cells.highlight | idents.hightlight"),
crayon_body(" have to be set to "),
crayon_key("NULL"),
crayon_body(".")))
if (order_and_shuffle_used){
warning(paste0(add_warning(), crayon_body("Setting up a custom order with paramter "),
crayon_key("order"),
crayon_body(" when "),
crayon_key("shuffle = TRUE"),
crayon_body(" might result in unexpected behaviors.\nPlease, consider using it alongside "),
crayon_key("shuffle = FALSE"),
crayon_body(".")), call. = FALSE)
}
# Check for label.color.
## Check for the colors assigned to the labels if label = TRUE.
check_colors(label.color, parameter_name = "label.color")
## Check the color assigned to NAs.
check_colors(na.value, parameter_name = "na.value")
## Check the color assigned to border.color.
check_colors(border.color, parameter_name = "border.color")
## Check the color assigned to contour.color.
check_colors(contour.color, parameter_name = "contour.color")
## If the user provides more than one color to na.value, stop the function.
assertthat::assert_that(length(na.value) == 1,
msg = paste0(add_cross(), crayon_body("Please, provide only "),
crayon_key("one color"),
crayon_body(" to parameter "),
crayon_key("na.value"),
crayon_body(".")))
## Check that the contour_expand_axes is between 0 and 1.
assertthat::assert_that(contour_expand_axes <= 1,
msg = paste0(add_cross(), crayon_body("Please, provide a value "),
crayon_key("lower or equal to 1"),
crayon_body(" to parameter "),
crayon_key("contour_expand_axes"),
crayon_body(".")))
assertthat::assert_that(contour_expand_axes >= 0,
msg = paste0(add_cross(), crayon_body("Please, provide a value "),
crayon_key("lower or equal to 1"),
crayon_body(" to parameter "),
crayon_key("contour_expand_axes"),
crayon_body(".")))
# If the user provides raster = TRUE but the pt.size is less than 1, warn it.
if (isTRUE(raster) & pt.size < 1){
warning(paste0(add_warning(), crayon_body("Setting "),
crayon_key("raster = TRUE"),
crayon_body(" and "),
crayon_key("pt.size < 1"),
crayon_body("will result in the cells being plotted as a "),
crayon_key("cross"),
crayon_body(" instead of dots.\nThis behaviour can not be modified, but can be avoided by using "),
crayon_key("pt.size >= 1"),
crayon_body(".")), call. = FALSE)
}
check_parameters(parameter = font.type, parameter_name = "font.type")
check_parameters(parameter = legend.position, parameter_name = "legend.position")
check_parameters(parameter = marginal.type, parameter_name = "marginal.type")
check_parameters(parameter = contour.lineend, parameter_name = "contour.lineend")
check_parameters(parameter = contour.linejoin, parameter_name = "contour.linejoin")
check_parameters(parameter = contour.position, parameter_name = "contour.position")
check_parameters(parameter = border.density, parameter_name = "border.density")
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")
# If the user has not provided colors.
if (is.null(colors.use)){
colors.use <- {
# Default parameters.
default_parameters <- is.null(group.by) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Group.by was used.
group_by_is_used <- !(is.null(group.by)) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Split.by was used.
split_by_is_used <- is.null(group.by) & !(is.null(split.by)) & is.null(cells.highlight) & is.null(idents.highlight)
# Cells.highlight or idents.highlight was used.
highlighting_cells <- is.null(group.by) & is.null(split.by) & (!(is.null(cells.highlight)) | !(is.null(idents.highlight)))
if (isTRUE(default_parameters)){
# Generate the color scale based on the levels assigned to the sample.
generate_color_scale(levels(sample))
} else if (isTRUE(group_by_is_used) | isTRUE(group_by_and_split_by_used)){
# Retrieve the unique values in group.by metadata variable.
data.use <- sample[[]][, group.by, drop = FALSE]
# If the variable is a factor, use the levels as order. If not, order the values alphabetically.
names.use <- if (is.factor(data.use[, 1])){levels(data.use[, 1])} else {sort(unique(data.use[, 1]))}
# Generate the color scale to be used based on the unique values of group.by.
generate_color_scale(names.use)
} else if (isTRUE(split_by_is_used)){
# Retrieve the unique values in split.by metadata variable.
data.use <- sample[[]][, split.by, drop = FALSE]
# If the variable is a factor, use the levels as order. If not, order the values alphabetically.
names.use <- if (is.factor(data.use[, 1])){levels(data.use[, 1])} else {sort(unique(data.use[, 1]))}
# Generate the color scale based on the unique values of split.by
generate_color_scale(names.use)
} else if (isTRUE(highlighting_cells)){
# If the user wants to highlight some cells, use this color.
colors.use <- "#0A305F"
}
}
# For split.by + group.by cases.
colors.use.original <- colors.use
# But, if the user has provided a custom color palette.
} else {
# Check that the provided values are valid color representations.
check_colors(colors.use, parameter_name = "colors.use")
# If no further parameters are used.
default_parameters <- is.null(group.by) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Group.by was used.
group_by_is_used <- !(is.null(group.by)) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Split.by was used.
split_by_is_used <- is.null(group.by) & !(is.null(split.by)) & is.null(cells.highlight) & is.null(idents.highlight)
# When either cells.highlight or idents.highlight was used.
highlighting_cells <- is.null(group.by) & is.null(split.by) & (!(is.null(cells.highlight)) | !(is.null(idents.highlight)))
# For split.by + group.by cases.
colors.use.original <- colors.use
# When running under default parameters.
if (isTRUE(default_parameters)){
# Check that the color palette has the right amount of named colors with regards to the current identities.
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
idents.keep = idents.keep)
# When using group.by or a combination of group.by and split.by.
} else if (isTRUE(group_by_is_used) | isTRUE(group_by_and_split_by_used)){
# Check that the color palette has the right amount of named colors with regards to group.by values.
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = group.by,
idents.keep = idents.keep)
# When using split.by.
} else if (isTRUE(split_by_is_used)){
# Check that the color palette has the right amount of named colors with regards to split.by values.
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = split.by,
idents.keep = idents.keep)
# When highlighting cells.
} else if (isTRUE(highlighting_cells)){
# Stop the execution if more than one color is provided to highlight the cells.
assertthat::assert_that(length(colors.use) == 1,
msg = paste0(add_cross(), crayon_body("Please, provide only "),
crayon_key("one color"),
crayon_body(" to "),
crayon_key("cells.highlight"),
crayon_body(" or "),
crayon_key("idents.highlight"),
crayon_body(".")))
}
}
# Compute the colors for the labels.
if (isTRUE(label)){
if (isTRUE(label.box)){
if (is.null(label.fill)){
colors.use.label.fill <- colors.use
} else {
# Check that only one color has been provided to label.fill.
assertthat::assert_that(length(label.fill) == 1,
msg = paste0(add_cross(), crayon_body("Please, provide only "),
crayon_key("one color"),
crayon_body(" to "),
crayon_key("label.fill"),
crayon_body(" or "),
crayon_key("NULL"),
crayon_body(".")))
# And check that is a valid color.
check_colors(label.fill, parameter_name = "label.fill")
colors.use.label.fill <- rep(label.fill, length(colors.use))
}
}
}
# Set cells to NA according to idents.keep.
# If the user does not want to highlight cells or split by identities but wants to remove some identities.
idents_keep_used <- is.null(cells.highlight) & is.null(idents.highlight) & !(is.null(idents.keep))
if (isTRUE(idents_keep_used)){
# CONDITION: both group.by and split.by are not used.
group_by_and_split_by_are_null <- is.null(group.by) & is.null(split.by)
# CONDITION: group.by is used.
group_by_is_used <- !(is.null(group.by)) & is.null(split.by)
# CONDITION: split.by is used.
split_by_is_used <- is.null(group.by) & !(is.null(split.by))
# When running under default parameters.
if (isTRUE(group_by_and_split_by_are_null)){
# Check that idents.keep matches the values and if not, stop the execution.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% levels(sample))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in "),
crayon_key("levels(sample"),
crayon_body(".")))
# Set the identities that the user wants to exclude as NA.
Seurat::Idents(sample)[!(Seurat::Idents(sample) %in% idents.keep)] <- NA
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
idents.keep = idents.keep)
# If split.by is used instead.
} else if (group_by_and_split_by_used){
# Check that the values in idents.keep are in the unique values of split.by.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% unique(sample@meta.data[, split.by]))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in the "),
crayon_key("split.by"),
crayon_body(" metadata provided.")))
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = group.by)
} else if (split_by_is_used){
# Check that the values in idents.keep are in the unique values of split.by.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% unique(sample@meta.data[, split.by]))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in the "),
crayon_key("split.by"),
crayon_body(" metadata provided.")))
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = split.by,
idents.keep = idents.keep)
# When using group.by, check with the values in group.by.
} else if (group_by_is_used) {
# Check that idents.keep matches the values, if not, stop the execution.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% unique(sample@meta.data[, group.by]))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in the "),
crayon_key("group.by"),
crayon_body(" metadata variable provided.")))
# Convert to NA values in group.by not included in the user's selected values.
sample@meta.data[, group.by][!(sample@meta.data[, group.by] %in% idents.keep)] <- NA
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = group.by,
idents.keep = idents.keep)
}
}
# Generate base layer.
out <- compute_umap_layer(sample = sample,
labels = colnames(sample@reductions[[reduction]][[]])[dims],
pt.size = pt.size,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
na.value = na.value,
n = 100)
base_layer <- out$base_layer
na_layer <- out$na_layer
# PLOTTING
# If raster = TRUE, add 1 to pt.size to keep consistency between plots.
# If the UMAP does not need to be split in multiple panes (default case).
# CONDITION: Not highligting cells and not using split.by.
not_highlighting_and_not_split_by <- is.null(cells.highlight) & is.null(idents.highlight) & is.null(split.by)
# CONDITION: Using split.by.
split_by_used <- is.null(cells.highlight) & is.null(idents.highlight) & !(is.null(split.by))
# CONDITION: highlighting cells.
highlighting_cells <- !(is.null(cells.highlight)) | !(is.null(idents.highlight))
# When running under default parameters or using group.by
if (not_highlighting_and_not_split_by){
if (utils::packageVersion("Seurat") >= "4.1.0"){
p <- Seurat::DimPlot(if (is.null(idents.keep)) {sample} else {if (is.null(group.by)) {sample[, Seurat::Idents(sample) %in% idents.keep]} else {sample[, sample@meta.data[, group.by] %in% idents.keep]}},
reduction = reduction,
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
group.by = group.by,
cols = colors.use,
raster = raster,
raster.dpi = c(raster.dpi, raster.dpi),
ncol = ncol)
} else { # nocov start
p <- Seurat::DimPlot(if (is.null(idents.keep)) {sample} else {if (is.null(group.by)) {sample[, Seurat::Idents(sample) %in% idents.keep]} else {sample[, sample@meta.data[, group.by] %in% idents.keep]}},
reduction = reduction,
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
group.by = group.by,
cols = colors.use,
raster = raster,
ncol = ncol)
} # nocov end
p <- p &
ggplot2::guides(color = ggplot2::guide_legend(ncol = legend.ncol,
nrow = legend.nrow,
byrow = legend.byrow,
override.aes = list(size = legend.icon.size),
title = legend.title,
title.position = legend.title.position))
if (isTRUE(label)){
if (isTRUE(label.box)){
if (is.null(label.fill)){
colors.use.label.fill <- colors.use
} else {
colors.use.label.fill <- rep(label.fill, length(colors.use))
}
p <- add_scale(p = p,
function_use = ggplot2::scale_fill_manual(values = colors.use.label.fill),
scale = "fill")
}
p$layers[[length(p$layers)]]$aes_params$fontface <- "bold"
}
if (!(is.null(group.by))){
# Remove automatic title inserted by Seurat.
p <- p & ggplot2::ggtitle("")
}
# Add another layer of black dots to make the colored ones stand up.
if (!is.null(idents.keep)){
if (isTRUE(plot_cell_borders)){
sample.use <- if (is.null(group.by)) {sample[, Seurat::Idents(sample) %in% idents.keep]} else {sample[, sample@meta.data[, group.by] %in% idents.keep]}
out <- compute_umap_layer(sample = sample.use,
labels = colnames(sample.use@reductions[[reduction]][[]])[dims],
pt.size = pt.size,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
na.value = na.value,
n = 100)
base_layer.subset <- out$base_layer
p$layers <- append(base_layer.subset, p$layers)
}
# Add NA layer.
p$layers <- append(na_layer, p$layers)
}
# Add cell borders.
if (isTRUE(plot_cell_borders)){
p$layers <- append(base_layer, p$layers)
}
if (isTRUE(plot_density_contour)){
data <- ggplot2::ggplot_build(p)
density_layer <- ggplot2::stat_density_2d(data = data$data[[1]],
mapping = ggplot2::aes(x = .data$x,
y = .data$y),
color = contour.color,
lineend = contour.lineend,
linejoin = contour.linejoin)
if (contour.position == "bottom"){
p$layers <- append(density_layer, p$layers)
} else if (contour.position == "top"){
p$layers <- append(p$layers, density_layer)
}
min_x <- min(data$data[[1]]$x) * (1 + contour_expand_axes)
max_x <- max(data$data[[1]]$x) * (1 + contour_expand_axes)
min_y <- min(data$data[[1]]$y) * (1 + contour_expand_axes)
max_y <- max(data$data[[1]]$y) * (1 + contour_expand_axes)
# Expand axes limits to allocate the new contours.
suppressMessages({
p <- p +
ggplot2::xlim(c(min_x, max_x)) +
ggplot2::ylim(c(min_y, max_y))
})
}
# Add theme settings to all plots.
p <- p &
ggplot2::theme_minimal(base_size = font.size) &
ggplot2::theme(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),
plot.title.position = "plot",
plot.caption.position = "plot",
text = ggplot2::element_text(family = font.type),
legend.justification = "center",
legend.text = ggplot2::element_text(face = legend.text.face),
legend.title = if (legend.position != "none") {ggplot2::element_text(face = legend.title.face)} else {ggplot2::element_blank()},
legend.position = legend.position,
panel.grid = ggplot2::element_blank(),
plot.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0),
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"))
} else if (isTRUE(group_by_and_split_by_used) | isTRUE(split_by_used)){
list.plots <- list()
unique_values <- if(is.factor(sample@meta.data[, split.by])){levels(sample@meta.data[, split.by])} else {sort(unique(sample@meta.data[, split.by]))}
if (!is.null(idents.keep)){
unique_values <- unique_values[unique_values %in% idents.keep]
}
# If group.by and split.by are used, add a general view that will have a legend with all parameters.
p.extra <- do_DimPlot(sample = sample,
reduction = reduction,
group.by = ifelse(isTRUE(group_by_and_split_by_used), group.by, split.by),
split.by = NULL,
colors.use = colors.use.original,
shuffle = shuffle,
order = order,
raster = raster,
pt.size = pt.size,
label = label,
label.color = label.color,
label.fill = label.fill,
label.size = label.size,
label.box = label.box,
repel = repel,
cells.highlight = NULL,
idents.highlight = NULL,
idents.keep = NULL,
sizes.highlight = sizes.highlight,
ncol = ncol,
plot.title = "Combined",
plot.subtitle = NULL,
plot.caption = NULL,
legend.title = legend.title,
legend.position = legend.position,
legend.title.position = legend.title.position,
legend.ncol = legend.ncol,
legend.nrow = legend.nrow,
legend.icon.size = legend.icon.size,
legend.byrow = legend.byrow,
raster.dpi = raster.dpi,
dims = dims,
font.size = font.size,
font.type = font.type,
na.value = na.value,
plot_cell_borders = plot_cell_borders,
border.size = border.size,
border.color = border.color,
border.density = border.density,
plot_marginal_distributions = plot_marginal_distributions,
marginal.type = marginal.type,
marginal.size = marginal.size,
marginal.group = marginal.group,
plot.axes = plot.axes,
plot_density_contour = plot_density_contour,
contour.position = contour.position,
contour.color = contour.color,
contour.lineend = contour.lineend,
contour.linejoin = contour.linejoin,
contour_expand_axes = contour_expand_axes,
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)
p.extra <- p.extra + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5))
# Add plot to list.
list.plots[[1]] <- p.extra
num_values <- length(unique_values)
for (i in seq_len(num_values)){
value <- unique_values[i]
# Generate a middle layer for the missing values after split.by.
sample.use <- sample[, sample@meta.data[, split.by] == value]
if (utils::packageVersion("Seurat") >= "4.1.0"){
p.loop <- Seurat::DimPlot(sample.use,
reduction = reduction,
group.by = if (is.null(group.by)) {split.by} else {group.by},
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
cols = colors.use,
raster = raster,
raster.dpi = c(raster.dpi, raster.dpi))
} else { # nocov start
p.loop <- Seurat::DimPlot(sample.use,
reduction = reduction,
group.by = if (is.null(group.by)) {split.by} else {group.by},
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
cols = colors.use,
raster = raster)
} # nocov end
p.loop <- p.loop +
ggplot2::ggtitle(value) +
ggplot2::guides(color = ggplot2::guide_legend(title = legend.title,
ncol = legend.ncol,
nrow = legend.nrow,
byrow = legend.byrow,
override.aes = list(size = legend.icon.size),
title.position = legend.title.position))
if (isTRUE(label)){
if (isTRUE(label.box)){
p.loop <- add_scale(p = p.loop,
function_use = ggplot2::scale_fill_manual(values = colors.use.label.fill),
scale = "fill")
}
p.loop$layers[[length(p.loop$layers)]]$aes_params$fontface <- "bold"
}
# Add another layer of black dots to make the colored ones stand up.
if (isTRUE(plot_cell_borders)){
out <- compute_umap_layer(sample = sample.use,
labels = colnames(sample.use@reductions[[reduction]][[]])[dims],
pt.size = pt.size,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
na.value = na.value,
n = 100)
base_layer.subset <- out$base_layer
p.loop$layers <- append(base_layer.subset, p.loop$layers)
}
# Add NA layer.
p.loop$layers <- append(na_layer, p.loop$layers)
# Add cell borders.
if (isTRUE(plot_cell_borders)){
p.loop$layers <- append(base_layer, p.loop$layers)
suppressMessages({
p.loop <- p.loop +
ggplot2::scale_x_continuous(limits = c(min(p.loop$layers[[1]]$data$x),
max(p.loop$layers[[1]]$data$x))) +
ggplot2::scale_y_continuous(limits = c(min(p.loop$layers[[1]]$data$y),
max(p.loop$layers[[1]]$data$y)))
})
}
if (isTRUE(plot_density_contour)){
data <- ggplot2::ggplot_build(p.loop)
density_layer <- ggplot2::stat_density_2d(data = data$data[[1]],
mapping = ggplot2::aes(x = .data$x,
y = .data$y),
color = contour.color,
lineend = contour.lineend,
linejoin = contour.linejoin)
if (contour.position == "bottom"){
p.loop$layers <- append(density_layer, p.loop$layers)
} else if (contour.position == "top"){
p.loop$layers <- append(p.loop$layers, density_layer)
}
min_x <- min(data$data[[1]]$x) * (1 + contour_expand_axes)
max_x <- max(data$data[[1]]$x) * (1 + contour_expand_axes)
min_y <- min(data$data[[1]]$y) * (1 + contour_expand_axes)
max_y <- max(data$data[[1]]$y) * (1 + contour_expand_axes)
# Expand axes limits to allocate the new contours.
suppressMessages({
p.loop <- p.loop +
ggplot2::xlim(c(min_x, max_x)) +
ggplot2::ylim(c(min_y, max_y))
})
}
p.loop <- p.loop +
ggplot2::theme_minimal(base_size = font.size) +
ggplot2::theme(plot.title = ggplot2::element_text(face = plot.title.face, hjust = 0.5),
plot.subtitle = ggplot2::element_text(face = plot.subtitle.face, hjust = 0),
plot.caption = ggplot2::element_text(face = plot.caption.face, hjust = 1),
plot.title.position = "plot",
plot.caption.position = "plot",
text = ggplot2::element_text(family = font.type),
legend.justification = "center",
legend.text = ggplot2::element_text(face = legend.text.face),
legend.title = if (legend.position != "none") {ggplot2::element_text(face = legend.title.face)} else {ggplot2::element_blank()},
panel.grid = ggplot2::element_blank(),
plot.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0),
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"),
legend.position = "none")
list.plots[[value]] <- p.loop
}
p <- patchwork::wrap_plots(list.plots, ncol = ncol, guides = "collect")
p <- p +
patchwork::plot_annotation(theme = ggplot2::theme(legend.position = legend.position))
}
# If the user wants to highlight some of the cells.
else if (highlighting_cells){
# Compute the cells to highlight.
if (is.null(idents.highlight) & !(is.null(cells.highlight))){
# Only if cells.highlight parameters is used.
cells.use <- cells.highlight
} else if (!(is.null(idents.highlight)) & is.null(cells.highlight)){
# Only if idents.highlight parameter is used.
# Check if the provided identities are part of the active identities in the object.
check_identity(sample = sample, identities = idents.highlight)
cells.use <- names(Seurat::Idents(sample)[Seurat::Idents(sample) %in% idents.highlight])
} else if (!(is.null(idents.highlight)) & !(is.null(cells.highlight))){
# Check if the provided identities are part of the active identities in the object.
check_identity(sample = sample, identities = idents.highlight)
# Both idents.highlight and cells.highlight are used.
cells.1 <- cells.highlight
cells.2 <- names(Seurat::Idents(sample)[Seurat::Idents(sample) %in% idents.highlight])
cells.use <- unique(c(cells.1, cells.2))
}
sample$selected_cells <- ifelse(colnames(sample) %in% cells.use, "Selected cells", NA)
colors.use.highlight <- c("Selected cells" = colors.use)
if (utils::packageVersion("Seurat") >= "4.1.0"){
p <- Seurat::DimPlot(sample[, cells.use],
reduction = reduction,
group.by = "selected_cells",
dims = dims,
pt.size = pt.size,
raster = raster,
raster.dpi = c(raster.dpi, raster.dpi),
ncol = ncol,
cols = colors.use.highlight,
na.value = "#bfbfbf00")
} else { # nocov start
p <- Seurat::DimPlot(sample[, cells.use],
group.by = "selected_cells",
reduction = reduction,
dims = dims,
pt.size = pt.size,
raster = raster,
ncol = ncol,
cols = colors.use.highlight,
na.value = "#bfbfbf00")
} # nocov end
p <- p &
ggplot2::ggtitle("") &
ggplot2::guides(color = ggplot2::guide_legend(title = legend.title,
ncol = legend.ncol,
nrow = legend.nrow,
byrow = legend.byrow,
override.aes = list(size = legend.icon.size),
title.position = legend.title.position))
# Add cell borders.
if (isTRUE(plot_cell_borders)){
# Compute extra layer for the highlighted cells.
out <- compute_umap_layer(sample = sample[, cells.use],
labels = colnames(sample[, cells.use]@reductions[[reduction]][[]])[dims],
pt.size = sizes.highlight,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
n = 100)
base_layer_subset <- out$base_layer
p$layers <- append(base_layer_subset, p$layers)
p$layers <- append(na_layer, p$layers)
p$layers <- append(base_layer, p$layers)
suppressMessages({
p <- p +
ggplot2::scale_x_continuous(limits = c(min(p$layers[[1]]$data$x),
max(p$layers[[1]]$data$x))) +
ggplot2::scale_y_continuous(limits = c(min(p$layers[[1]]$data$y),
max(p$layers[[1]]$data$y)))
})
}
if (isTRUE(plot_density_contour)){
data <- ggplot2::ggplot_build(p)
density_layer <- ggplot2::stat_density_2d(data = data$data[[1]],
mapping = ggplot2::aes(x = .data$x,
y = .data$y),
color = contour.color,
lineend = contour.lineend,
linejoin = contour.linejoin)
if (contour.position == "bottom"){
p$layers <- append(density_layer, p$layers)
} else if (contour.position == "top"){
p$layers <- append(p$layers, density_layer)
}
min_x <- min(data$data[[1]]$x) * (1 + contour_expand_axes)
max_x <- max(data$data[[1]]$x) * (1 + contour_expand_axes)
min_y <- min(data$data[[1]]$y) * (1 + contour_expand_axes)
max_y <- max(data$data[[1]]$y) * (1 + contour_expand_axes)
# Expand axes limits to allocate the new contours.
suppressMessages({
p <- p +
ggplot2::xlim(c(min_x, max_x)) +
ggplot2::ylim(c(min_y, max_y))
})
}
# Titles in split.by are centered by default.
hjust_use <- if(split_by_used){0.5} else {0}
# Add theme settings to all plots.
p <- p &
ggplot2::theme_minimal(base_size = font.size) &
ggplot2::theme(plot.title = ggplot2::element_text(face = plot.title.face, hjust = hjust_use),
plot.subtitle = ggplot2::element_text(face = plot.subtitle.face, hjust = 0),
plot.caption = ggplot2::element_text(face = plot.caption.face, hjust = 1),
plot.title.position = "plot",
plot.caption.position = "plot",
text = ggplot2::element_text(family = font.type),
legend.justification = "center",
legend.text = ggplot2::element_text(face = legend.text.face),
legend.title = if (legend.position != "none") {ggplot2::element_text(face = legend.title.face)} else {ggplot2::element_blank()},
legend.position = legend.position,
panel.grid = ggplot2::element_blank(),
plot.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0),
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"))
}
# Add plot title to the plots.
if (!is.null(plot.title)){
if (!(is.null(split.by))){
p <- p +
patchwork::plot_annotation(title = plot.title)
} else {
p <- p &
ggplot2::labs(title = plot.title)
}
}
# Add plot subtitle to the plots.
if (!is.null(plot.subtitle)){
if (!(is.null(split.by))){
p <- p +
patchwork::plot_annotation(subtitle = plot.subtitle)
} else {
p <- p +
ggplot2::labs(subtitle = plot.subtitle)
}
}
# Add plot caption to the plots.
if (!is.null(plot.caption)){
if (!(is.null(split.by))){
p <- p +
patchwork::plot_annotation(caption = plot.caption)
} else {
p <- p +
ggplot2::labs(caption = plot.caption)
}
}
if (base::isFALSE(plot.axes)){
p <- p &
ggplot2::theme(axis.title = ggplot2::element_blank(),
axis.text = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
axis.line = ggplot2::element_blank())
} else {
p <- p &
ggplot2::theme(axis.title = ggplot2::element_text(face = axis.title.face),
axis.text = ggplot2::element_text(face = axis.text.face),
axis.ticks = ggplot2::element_line(color = "black"),
axis.line = ggplot2::element_line(color = "black"))
}
# Add marginal plots.
if (not_highlighting_and_not_split_by & isTRUE(plot_marginal_distributions & base::isFALSE(plot_cell_borders))){
# Remove annoying warnings when violin is used as marginal distribution.
if (marginal.type == "violin"){
p <- suppressWarnings({ggExtra::ggMarginal(p = p,
groupColour = ifelse(isTRUE(marginal.group), TRUE, FALSE),
groupFill = ifelse(isTRUE(marginal.group), TRUE, FALSE),
type = marginal.type,
size = marginal.size)})
} else {
p <- ggExtra::ggMarginal(p = p,
groupColour = ifelse(isTRUE(marginal.group), TRUE, FALSE),
groupFill = ifelse(isTRUE(marginal.group), TRUE, FALSE),
type = marginal.type,
size = marginal.size)
}
# Transform back to ggplot2 object.
p <- ggplotify::as.ggplot(p)
# Fix for the plot backgrounds after applying ggMarginal.
p$theme$plot.background <- ggplot2::element_rect(fill = "white", color = "white")
p$theme$legend.background <- ggplot2::element_rect(fill = "white", color = "white")
p$theme$panel.background <- ggplot2::element_rect(fill = "white", color = "white")
} else if (isTRUE(plot_marginal_distributions)) {
stop(paste0(add_cross(),
crayon_body("Marginal distributions can not be used alongside when splitting by categories ("),
crayon_key("split.by"),
crayon_body("), highlighting cells ("),
crayon_key("cells.highlight/idents.highlight"),
crayon_body(") or plotting cell borders ("),
crayon_key("plot_cell_borders"),
crayon_body(").")), call. = FALSE)
}
# Return the final plot.
return(p)
}
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R Package Documentation
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Defines functions do_DimPlot
Documented in do_DimPlot
#' Wrapper for \link[Seurat]{DimPlot}.
#'
#' @inheritParams doc_function
#' @param idents.keep \strong{\code{\link[base]{character}}} | Vector of identities to keep. This will effectively set the rest of the cells that do not match the identities provided to NA, therefore coloring them according to na.value parameter.
#' @param shuffle \strong{\code{\link[base]{logical}}} | Whether to shuffle the cells or not, so that they are not plotted cluster-wise. Recommended.
#' @param order \strong{\code{\link[base]{character}}} | Vector of identities to be plotted. Either one with all identities or just some, which will be plotted last.
#' @param sizes.highlight \strong{\code{\link[base]{numeric}}} | Point size of highlighted cells using cells.highlight parameter.
#' @return A ggplot2 object containing a DimPlot.
#' @export
#'
#' @example man/examples/examples_do_DimPlot.R
do_DimPlot <- function(sample,
reduction = NULL,
group.by = NULL,
split.by = NULL,
colors.use = NULL,
shuffle = TRUE,
order = NULL,
raster = FALSE,
pt.size = 1,
label = FALSE,
label.color = "black",
label.fill = "white",
label.size = 4,
label.box = TRUE,
repel = FALSE,
cells.highlight = NULL,
idents.highlight = NULL,
idents.keep = NULL,
sizes.highlight = 1,
ncol = NULL,
plot.title = NULL,
plot.subtitle = NULL,
plot.caption = NULL,
legend.title = NULL,
legend.position = "bottom",
legend.title.position = "top",
legend.ncol = NULL,
legend.nrow = NULL,
legend.icon.size = 4,
legend.byrow = FALSE,
raster.dpi = 2048,
dims = c(1, 2),
font.size = 14,
font.type = "sans",
na.value = "grey75",
plot_cell_borders = TRUE,
border.size = 2,
border.color = "black",
border.density = 1,
plot_marginal_distributions = FALSE,
marginal.type = "density",
marginal.size = 5,
marginal.group = TRUE,
plot.axes = FALSE,
plot_density_contour = FALSE,
contour.position = "bottom",
contour.color = "grey90",
contour.lineend = "butt",
contour.linejoin = "round",
contour_expand_axes = 0.25,
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_DimPlot")
# Check if the sample provided is a Seurat object.
check_Seurat(sample = sample)
sample <- check_Assay5(sample)
# Check the reduction.
reduction <- check_and_set_reduction(sample = sample, reduction = reduction)
# Check the dimensions.
dims <- check_and_set_dimensions(sample = sample, reduction = reduction, dims = dims)
# Check logical parameters.
logical_list <- list("label" = label,
"repel" = repel,
"shuffle" = shuffle,
"legend.byrow" = legend.byrow,
"raster" = raster,
"plot_marginal_distributions" = plot_marginal_distributions,
"marginal.group" = marginal.group,
"plot_cell_borders" = plot_cell_borders,
"plot.axes" = plot.axes,
"plot_density_contour" = plot_density_contour,
"label.box" = label.box)
check_type(parameters = logical_list, required_type = "logical", test_function = is.logical)
# Check numeric parameters.
numeric_list <- list("pt.size" = pt.size,
"sizes.highlight" = sizes.highlight,
"legend.ncol" = legend.ncol,
"legend.nrow" = legend.nrow,
"font.size" = font.size,
"legend.icon.size" = legend.icon.size,
"ncol" = ncol,
"raster.dpi" = raster.dpi,
"marginal.size" = marginal.size,
"border.size" = border.size,
"contour_expand_axes" = contour_expand_axes,
"label.size" = label.size,
"border.density" = border.density)
check_type(parameters = numeric_list, required_type = "numeric", test_function = is.numeric)
# Check character parameters.
character_list <- list("legend.position" = legend.position,
"plot.title" = plot.title,
"plot.subtitle" = plot.subtitle,
"plot.caption" = plot.caption,
"legend.title" = legend.title,
"cells.highlight" = cells.highlight,
"idents.keep" = idents.keep,
"order" = order,
"na.value" = na.value,
"idents.highlight" = idents.highlight,
"legend.title.position" = legend.title.position,
"font.type" = font.type,
"marginal.type" = marginal.type,
"border.color" = border.color,
"contour.position" = contour.position,
"contour.color" = contour.color,
"contour.lineend" = contour.lineend,
"contour.linejoin" = contour.linejoin,
"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)
# Checks to ensure proper function.
group_by_and_split_by_used <- !(is.null(split.by)) & !(is.null(group.by))
group_by_and_highlighting_cells <- (!(is.null(cells.highlight)) | !(is.null(idents.highlight))) & !(is.null(group.by))
split_by_and_highlighting_cells <- (!(is.null(cells.highlight)) | !(is.null(idents.highlight))) & !(is.null(split.by))
order_and_shuffle_used <- !(is.null(order)) & isTRUE(shuffle)
assertthat::assert_that(!group_by_and_highlighting_cells,
msg = paste0(add_cross(), crayon_body("Either "),
crayon_key("group.by"),
crayon_body(" or "),
crayon_key("cells.highlight | idents.hightlight"),
crayon_body(" have to be set to "),
crayon_key("NULL"),
crayon_body(".")))
assertthat::assert_that(!split_by_and_highlighting_cells,
msg = paste0(add_cross(), crayon_body("Either "),
crayon_key("split.by"),
crayon_body(" or "),
crayon_key("cells.highlight | idents.hightlight"),
crayon_body(" have to be set to "),
crayon_key("NULL"),
crayon_body(".")))
if (order_and_shuffle_used){
warning(paste0(add_warning(), crayon_body("Setting up a custom order with paramter "),
crayon_key("order"),
crayon_body(" when "),
crayon_key("shuffle = TRUE"),
crayon_body(" might result in unexpected behaviors.\nPlease, consider using it alongside "),
crayon_key("shuffle = FALSE"),
crayon_body(".")), call. = FALSE)
}
# Check for label.color.
## Check for the colors assigned to the labels if label = TRUE.
check_colors(label.color, parameter_name = "label.color")
## Check the color assigned to NAs.
check_colors(na.value, parameter_name = "na.value")
## Check the color assigned to border.color.
check_colors(border.color, parameter_name = "border.color")
## Check the color assigned to contour.color.
check_colors(contour.color, parameter_name = "contour.color")
## If the user provides more than one color to na.value, stop the function.
assertthat::assert_that(length(na.value) == 1,
msg = paste0(add_cross(), crayon_body("Please, provide only "),
crayon_key("one color"),
crayon_body(" to parameter "),
crayon_key("na.value"),
crayon_body(".")))
## Check that the contour_expand_axes is between 0 and 1.
assertthat::assert_that(contour_expand_axes <= 1,
msg = paste0(add_cross(), crayon_body("Please, provide a value "),
crayon_key("lower or equal to 1"),
crayon_body(" to parameter "),
crayon_key("contour_expand_axes"),
crayon_body(".")))
assertthat::assert_that(contour_expand_axes >= 0,
msg = paste0(add_cross(), crayon_body("Please, provide a value "),
crayon_key("lower or equal to 1"),
crayon_body(" to parameter "),
crayon_key("contour_expand_axes"),
crayon_body(".")))
# If the user provides raster = TRUE but the pt.size is less than 1, warn it.
if (isTRUE(raster) & pt.size < 1){
warning(paste0(add_warning(), crayon_body("Setting "),
crayon_key("raster = TRUE"),
crayon_body(" and "),
crayon_key("pt.size < 1"),
crayon_body("will result in the cells being plotted as a "),
crayon_key("cross"),
crayon_body(" instead of dots.\nThis behaviour can not be modified, but can be avoided by using "),
crayon_key("pt.size >= 1"),
crayon_body(".")), call. = FALSE)
}
check_parameters(parameter = font.type, parameter_name = "font.type")
check_parameters(parameter = legend.position, parameter_name = "legend.position")
check_parameters(parameter = marginal.type, parameter_name = "marginal.type")
check_parameters(parameter = contour.lineend, parameter_name = "contour.lineend")
check_parameters(parameter = contour.linejoin, parameter_name = "contour.linejoin")
check_parameters(parameter = contour.position, parameter_name = "contour.position")
check_parameters(parameter = border.density, parameter_name = "border.density")
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")
# If the user has not provided colors.
if (is.null(colors.use)){
colors.use <- {
# Default parameters.
default_parameters <- is.null(group.by) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Group.by was used.
group_by_is_used <- !(is.null(group.by)) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Split.by was used.
split_by_is_used <- is.null(group.by) & !(is.null(split.by)) & is.null(cells.highlight) & is.null(idents.highlight)
# Cells.highlight or idents.highlight was used.
highlighting_cells <- is.null(group.by) & is.null(split.by) & (!(is.null(cells.highlight)) | !(is.null(idents.highlight)))
if (isTRUE(default_parameters)){
# Generate the color scale based on the levels assigned to the sample.
generate_color_scale(levels(sample))
} else if (isTRUE(group_by_is_used) | isTRUE(group_by_and_split_by_used)){
# Retrieve the unique values in group.by metadata variable.
data.use <- sample[[]][, group.by, drop = FALSE]
# If the variable is a factor, use the levels as order. If not, order the values alphabetically.
names.use <- if (is.factor(data.use[, 1])){levels(data.use[, 1])} else {sort(unique(data.use[, 1]))}
# Generate the color scale to be used based on the unique values of group.by.
generate_color_scale(names.use)
} else if (isTRUE(split_by_is_used)){
# Retrieve the unique values in split.by metadata variable.
data.use <- sample[[]][, split.by, drop = FALSE]
# If the variable is a factor, use the levels as order. If not, order the values alphabetically.
names.use <- if (is.factor(data.use[, 1])){levels(data.use[, 1])} else {sort(unique(data.use[, 1]))}
# Generate the color scale based on the unique values of split.by
generate_color_scale(names.use)
} else if (isTRUE(highlighting_cells)){
# If the user wants to highlight some cells, use this color.
colors.use <- "#0A305F"
}
}
# For split.by + group.by cases.
colors.use.original <- colors.use
# But, if the user has provided a custom color palette.
} else {
# Check that the provided values are valid color representations.
check_colors(colors.use, parameter_name = "colors.use")
# If no further parameters are used.
default_parameters <- is.null(group.by) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Group.by was used.
group_by_is_used <- !(is.null(group.by)) & is.null(split.by) & is.null(cells.highlight) & is.null(idents.highlight)
# Split.by was used.
split_by_is_used <- is.null(group.by) & !(is.null(split.by)) & is.null(cells.highlight) & is.null(idents.highlight)
# When either cells.highlight or idents.highlight was used.
highlighting_cells <- is.null(group.by) & is.null(split.by) & (!(is.null(cells.highlight)) | !(is.null(idents.highlight)))
# For split.by + group.by cases.
colors.use.original <- colors.use
# When running under default parameters.
if (isTRUE(default_parameters)){
# Check that the color palette has the right amount of named colors with regards to the current identities.
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
idents.keep = idents.keep)
# When using group.by or a combination of group.by and split.by.
} else if (isTRUE(group_by_is_used) | isTRUE(group_by_and_split_by_used)){
# Check that the color palette has the right amount of named colors with regards to group.by values.
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = group.by,
idents.keep = idents.keep)
# When using split.by.
} else if (isTRUE(split_by_is_used)){
# Check that the color palette has the right amount of named colors with regards to split.by values.
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = split.by,
idents.keep = idents.keep)
# When highlighting cells.
} else if (isTRUE(highlighting_cells)){
# Stop the execution if more than one color is provided to highlight the cells.
assertthat::assert_that(length(colors.use) == 1,
msg = paste0(add_cross(), crayon_body("Please, provide only "),
crayon_key("one color"),
crayon_body(" to "),
crayon_key("cells.highlight"),
crayon_body(" or "),
crayon_key("idents.highlight"),
crayon_body(".")))
}
}
# Compute the colors for the labels.
if (isTRUE(label)){
if (isTRUE(label.box)){
if (is.null(label.fill)){
colors.use.label.fill <- colors.use
} else {
# Check that only one color has been provided to label.fill.
assertthat::assert_that(length(label.fill) == 1,
msg = paste0(add_cross(), crayon_body("Please, provide only "),
crayon_key("one color"),
crayon_body(" to "),
crayon_key("label.fill"),
crayon_body(" or "),
crayon_key("NULL"),
crayon_body(".")))
# And check that is a valid color.
check_colors(label.fill, parameter_name = "label.fill")
colors.use.label.fill <- rep(label.fill, length(colors.use))
}
}
}
# Set cells to NA according to idents.keep.
# If the user does not want to highlight cells or split by identities but wants to remove some identities.
idents_keep_used <- is.null(cells.highlight) & is.null(idents.highlight) & !(is.null(idents.keep))
if (isTRUE(idents_keep_used)){
# CONDITION: both group.by and split.by are not used.
group_by_and_split_by_are_null <- is.null(group.by) & is.null(split.by)
# CONDITION: group.by is used.
group_by_is_used <- !(is.null(group.by)) & is.null(split.by)
# CONDITION: split.by is used.
split_by_is_used <- is.null(group.by) & !(is.null(split.by))
# When running under default parameters.
if (isTRUE(group_by_and_split_by_are_null)){
# Check that idents.keep matches the values and if not, stop the execution.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% levels(sample))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in "),
crayon_key("levels(sample"),
crayon_body(".")))
# Set the identities that the user wants to exclude as NA.
Seurat::Idents(sample)[!(Seurat::Idents(sample) %in% idents.keep)] <- NA
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
idents.keep = idents.keep)
# If split.by is used instead.
} else if (group_by_and_split_by_used){
# Check that the values in idents.keep are in the unique values of split.by.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% unique(sample@meta.data[, split.by]))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in the "),
crayon_key("split.by"),
crayon_body(" metadata provided.")))
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = group.by)
} else if (split_by_is_used){
# Check that the values in idents.keep are in the unique values of split.by.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% unique(sample@meta.data[, split.by]))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in the "),
crayon_key("split.by"),
crayon_body(" metadata provided.")))
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = split.by,
idents.keep = idents.keep)
# When using group.by, check with the values in group.by.
} else if (group_by_is_used) {
# Check that idents.keep matches the values, if not, stop the execution.
assertthat::assert_that(isTRUE(length(idents.keep) == sum(idents.keep %in% unique(sample@meta.data[, group.by]))),
msg = paste0(add_cross(), crayon_body("All the values in "),
crayon_key("idents.keep"),
crayon_body(" must be in the "),
crayon_key("group.by"),
crayon_body(" metadata variable provided.")))
# Convert to NA values in group.by not included in the user's selected values.
sample@meta.data[, group.by][!(sample@meta.data[, group.by] %in% idents.keep)] <- NA
colors.use <- check_consistency_colors_and_names(sample = sample,
colors = colors.use,
grouping_variable = group.by,
idents.keep = idents.keep)
}
}
# Generate base layer.
out <- compute_umap_layer(sample = sample,
labels = colnames(sample@reductions[[reduction]][[]])[dims],
pt.size = pt.size,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
na.value = na.value,
n = 100)
base_layer <- out$base_layer
na_layer <- out$na_layer
# PLOTTING
# If raster = TRUE, add 1 to pt.size to keep consistency between plots.
# If the UMAP does not need to be split in multiple panes (default case).
# CONDITION: Not highligting cells and not using split.by.
not_highlighting_and_not_split_by <- is.null(cells.highlight) & is.null(idents.highlight) & is.null(split.by)
# CONDITION: Using split.by.
split_by_used <- is.null(cells.highlight) & is.null(idents.highlight) & !(is.null(split.by))
# CONDITION: highlighting cells.
highlighting_cells <- !(is.null(cells.highlight)) | !(is.null(idents.highlight))
# When running under default parameters or using group.by
if (not_highlighting_and_not_split_by){
if (utils::packageVersion("Seurat") >= "4.1.0"){
p <- Seurat::DimPlot(if (is.null(idents.keep)) {sample} else {if (is.null(group.by)) {sample[, Seurat::Idents(sample) %in% idents.keep]} else {sample[, sample@meta.data[, group.by] %in% idents.keep]}},
reduction = reduction,
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
group.by = group.by,
cols = colors.use,
raster = raster,
raster.dpi = c(raster.dpi, raster.dpi),
ncol = ncol)
} else { # nocov start
p <- Seurat::DimPlot(if (is.null(idents.keep)) {sample} else {if (is.null(group.by)) {sample[, Seurat::Idents(sample) %in% idents.keep]} else {sample[, sample@meta.data[, group.by] %in% idents.keep]}},
reduction = reduction,
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
group.by = group.by,
cols = colors.use,
raster = raster,
ncol = ncol)
} # nocov end
p <- p &
ggplot2::guides(color = ggplot2::guide_legend(ncol = legend.ncol,
nrow = legend.nrow,
byrow = legend.byrow,
override.aes = list(size = legend.icon.size),
title = legend.title,
title.position = legend.title.position))
if (isTRUE(label)){
if (isTRUE(label.box)){
if (is.null(label.fill)){
colors.use.label.fill <- colors.use
} else {
colors.use.label.fill <- rep(label.fill, length(colors.use))
}
p <- add_scale(p = p,
function_use = ggplot2::scale_fill_manual(values = colors.use.label.fill),
scale = "fill")
}
p$layers[[length(p$layers)]]$aes_params$fontface <- "bold"
}
if (!(is.null(group.by))){
# Remove automatic title inserted by Seurat.
p <- p & ggplot2::ggtitle("")
}
# Add another layer of black dots to make the colored ones stand up.
if (!is.null(idents.keep)){
if (isTRUE(plot_cell_borders)){
sample.use <- if (is.null(group.by)) {sample[, Seurat::Idents(sample) %in% idents.keep]} else {sample[, sample@meta.data[, group.by] %in% idents.keep]}
out <- compute_umap_layer(sample = sample.use,
labels = colnames(sample.use@reductions[[reduction]][[]])[dims],
pt.size = pt.size,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
na.value = na.value,
n = 100)
base_layer.subset <- out$base_layer
p$layers <- append(base_layer.subset, p$layers)
}
# Add NA layer.
p$layers <- append(na_layer, p$layers)
}
# Add cell borders.
if (isTRUE(plot_cell_borders)){
p$layers <- append(base_layer, p$layers)
}
if (isTRUE(plot_density_contour)){
data <- ggplot2::ggplot_build(p)
density_layer <- ggplot2::stat_density_2d(data = data$data[[1]],
mapping = ggplot2::aes(x = .data$x,
y = .data$y),
color = contour.color,
lineend = contour.lineend,
linejoin = contour.linejoin)
if (contour.position == "bottom"){
p$layers <- append(density_layer, p$layers)
} else if (contour.position == "top"){
p$layers <- append(p$layers, density_layer)
}
min_x <- min(data$data[[1]]$x) * (1 + contour_expand_axes)
max_x <- max(data$data[[1]]$x) * (1 + contour_expand_axes)
min_y <- min(data$data[[1]]$y) * (1 + contour_expand_axes)
max_y <- max(data$data[[1]]$y) * (1 + contour_expand_axes)
# Expand axes limits to allocate the new contours.
suppressMessages({
p <- p +
ggplot2::xlim(c(min_x, max_x)) +
ggplot2::ylim(c(min_y, max_y))
})
}
# Add theme settings to all plots.
p <- p &
ggplot2::theme_minimal(base_size = font.size) &
ggplot2::theme(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),
plot.title.position = "plot",
plot.caption.position = "plot",
text = ggplot2::element_text(family = font.type),
legend.justification = "center",
legend.text = ggplot2::element_text(face = legend.text.face),
legend.title = if (legend.position != "none") {ggplot2::element_text(face = legend.title.face)} else {ggplot2::element_blank()},
legend.position = legend.position,
panel.grid = ggplot2::element_blank(),
plot.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0),
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"))
} else if (isTRUE(group_by_and_split_by_used) | isTRUE(split_by_used)){
list.plots <- list()
unique_values <- if(is.factor(sample@meta.data[, split.by])){levels(sample@meta.data[, split.by])} else {sort(unique(sample@meta.data[, split.by]))}
if (!is.null(idents.keep)){
unique_values <- unique_values[unique_values %in% idents.keep]
}
# If group.by and split.by are used, add a general view that will have a legend with all parameters.
p.extra <- do_DimPlot(sample = sample,
reduction = reduction,
group.by = ifelse(isTRUE(group_by_and_split_by_used), group.by, split.by),
split.by = NULL,
colors.use = colors.use.original,
shuffle = shuffle,
order = order,
raster = raster,
pt.size = pt.size,
label = label,
label.color = label.color,
label.fill = label.fill,
label.size = label.size,
label.box = label.box,
repel = repel,
cells.highlight = NULL,
idents.highlight = NULL,
idents.keep = NULL,
sizes.highlight = sizes.highlight,
ncol = ncol,
plot.title = "Combined",
plot.subtitle = NULL,
plot.caption = NULL,
legend.title = legend.title,
legend.position = legend.position,
legend.title.position = legend.title.position,
legend.ncol = legend.ncol,
legend.nrow = legend.nrow,
legend.icon.size = legend.icon.size,
legend.byrow = legend.byrow,
raster.dpi = raster.dpi,
dims = dims,
font.size = font.size,
font.type = font.type,
na.value = na.value,
plot_cell_borders = plot_cell_borders,
border.size = border.size,
border.color = border.color,
border.density = border.density,
plot_marginal_distributions = plot_marginal_distributions,
marginal.type = marginal.type,
marginal.size = marginal.size,
marginal.group = marginal.group,
plot.axes = plot.axes,
plot_density_contour = plot_density_contour,
contour.position = contour.position,
contour.color = contour.color,
contour.lineend = contour.lineend,
contour.linejoin = contour.linejoin,
contour_expand_axes = contour_expand_axes,
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)
p.extra <- p.extra + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5))
# Add plot to list.
list.plots[[1]] <- p.extra
num_values <- length(unique_values)
for (i in seq_len(num_values)){
value <- unique_values[i]
# Generate a middle layer for the missing values after split.by.
sample.use <- sample[, sample@meta.data[, split.by] == value]
if (utils::packageVersion("Seurat") >= "4.1.0"){
p.loop <- Seurat::DimPlot(sample.use,
reduction = reduction,
group.by = if (is.null(group.by)) {split.by} else {group.by},
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
cols = colors.use,
raster = raster,
raster.dpi = c(raster.dpi, raster.dpi))
} else { # nocov start
p.loop <- Seurat::DimPlot(sample.use,
reduction = reduction,
group.by = if (is.null(group.by)) {split.by} else {group.by},
label = label,
dims = dims,
repel = repel,
label.box = label.box,
label.color = label.color,
label.size = label.size,
na.value = na.value,
shuffle = shuffle,
order = order,
pt.size = pt.size,
cols = colors.use,
raster = raster)
} # nocov end
p.loop <- p.loop +
ggplot2::ggtitle(value) +
ggplot2::guides(color = ggplot2::guide_legend(title = legend.title,
ncol = legend.ncol,
nrow = legend.nrow,
byrow = legend.byrow,
override.aes = list(size = legend.icon.size),
title.position = legend.title.position))
if (isTRUE(label)){
if (isTRUE(label.box)){
p.loop <- add_scale(p = p.loop,
function_use = ggplot2::scale_fill_manual(values = colors.use.label.fill),
scale = "fill")
}
p.loop$layers[[length(p.loop$layers)]]$aes_params$fontface <- "bold"
}
# Add another layer of black dots to make the colored ones stand up.
if (isTRUE(plot_cell_borders)){
out <- compute_umap_layer(sample = sample.use,
labels = colnames(sample.use@reductions[[reduction]][[]])[dims],
pt.size = pt.size,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
na.value = na.value,
n = 100)
base_layer.subset <- out$base_layer
p.loop$layers <- append(base_layer.subset, p.loop$layers)
}
# Add NA layer.
p.loop$layers <- append(na_layer, p.loop$layers)
# Add cell borders.
if (isTRUE(plot_cell_borders)){
p.loop$layers <- append(base_layer, p.loop$layers)
suppressMessages({
p.loop <- p.loop +
ggplot2::scale_x_continuous(limits = c(min(p.loop$layers[[1]]$data$x),
max(p.loop$layers[[1]]$data$x))) +
ggplot2::scale_y_continuous(limits = c(min(p.loop$layers[[1]]$data$y),
max(p.loop$layers[[1]]$data$y)))
})
}
if (isTRUE(plot_density_contour)){
data <- ggplot2::ggplot_build(p.loop)
density_layer <- ggplot2::stat_density_2d(data = data$data[[1]],
mapping = ggplot2::aes(x = .data$x,
y = .data$y),
color = contour.color,
lineend = contour.lineend,
linejoin = contour.linejoin)
if (contour.position == "bottom"){
p.loop$layers <- append(density_layer, p.loop$layers)
} else if (contour.position == "top"){
p.loop$layers <- append(p.loop$layers, density_layer)
}
min_x <- min(data$data[[1]]$x) * (1 + contour_expand_axes)
max_x <- max(data$data[[1]]$x) * (1 + contour_expand_axes)
min_y <- min(data$data[[1]]$y) * (1 + contour_expand_axes)
max_y <- max(data$data[[1]]$y) * (1 + contour_expand_axes)
# Expand axes limits to allocate the new contours.
suppressMessages({
p.loop <- p.loop +
ggplot2::xlim(c(min_x, max_x)) +
ggplot2::ylim(c(min_y, max_y))
})
}
p.loop <- p.loop +
ggplot2::theme_minimal(base_size = font.size) +
ggplot2::theme(plot.title = ggplot2::element_text(face = plot.title.face, hjust = 0.5),
plot.subtitle = ggplot2::element_text(face = plot.subtitle.face, hjust = 0),
plot.caption = ggplot2::element_text(face = plot.caption.face, hjust = 1),
plot.title.position = "plot",
plot.caption.position = "plot",
text = ggplot2::element_text(family = font.type),
legend.justification = "center",
legend.text = ggplot2::element_text(face = legend.text.face),
legend.title = if (legend.position != "none") {ggplot2::element_text(face = legend.title.face)} else {ggplot2::element_blank()},
panel.grid = ggplot2::element_blank(),
plot.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0),
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"),
legend.position = "none")
list.plots[[value]] <- p.loop
}
p <- patchwork::wrap_plots(list.plots, ncol = ncol, guides = "collect")
p <- p +
patchwork::plot_annotation(theme = ggplot2::theme(legend.position = legend.position))
}
# If the user wants to highlight some of the cells.
else if (highlighting_cells){
# Compute the cells to highlight.
if (is.null(idents.highlight) & !(is.null(cells.highlight))){
# Only if cells.highlight parameters is used.
cells.use <- cells.highlight
} else if (!(is.null(idents.highlight)) & is.null(cells.highlight)){
# Only if idents.highlight parameter is used.
# Check if the provided identities are part of the active identities in the object.
check_identity(sample = sample, identities = idents.highlight)
cells.use <- names(Seurat::Idents(sample)[Seurat::Idents(sample) %in% idents.highlight])
} else if (!(is.null(idents.highlight)) & !(is.null(cells.highlight))){
# Check if the provided identities are part of the active identities in the object.
check_identity(sample = sample, identities = idents.highlight)
# Both idents.highlight and cells.highlight are used.
cells.1 <- cells.highlight
cells.2 <- names(Seurat::Idents(sample)[Seurat::Idents(sample) %in% idents.highlight])
cells.use <- unique(c(cells.1, cells.2))
}
sample$selected_cells <- ifelse(colnames(sample) %in% cells.use, "Selected cells", NA)
colors.use.highlight <- c("Selected cells" = colors.use)
if (utils::packageVersion("Seurat") >= "4.1.0"){
p <- Seurat::DimPlot(sample[, cells.use],
reduction = reduction,
group.by = "selected_cells",
dims = dims,
pt.size = pt.size,
raster = raster,
raster.dpi = c(raster.dpi, raster.dpi),
ncol = ncol,
cols = colors.use.highlight,
na.value = "#bfbfbf00")
} else { # nocov start
p <- Seurat::DimPlot(sample[, cells.use],
group.by = "selected_cells",
reduction = reduction,
dims = dims,
pt.size = pt.size,
raster = raster,
ncol = ncol,
cols = colors.use.highlight,
na.value = "#bfbfbf00")
} # nocov end
p <- p &
ggplot2::ggtitle("") &
ggplot2::guides(color = ggplot2::guide_legend(title = legend.title,
ncol = legend.ncol,
nrow = legend.nrow,
byrow = legend.byrow,
override.aes = list(size = legend.icon.size),
title.position = legend.title.position))
# Add cell borders.
if (isTRUE(plot_cell_borders)){
# Compute extra layer for the highlighted cells.
out <- compute_umap_layer(sample = sample[, cells.use],
labels = colnames(sample[, cells.use]@reductions[[reduction]][[]])[dims],
pt.size = sizes.highlight,
border.density = border.density,
border.size = border.size,
border.color = border.color,
raster = raster,
raster.dpi = raster.dpi,
reduction = reduction,
group.by = group.by,
split.by = split.by,
n = 100)
base_layer_subset <- out$base_layer
p$layers <- append(base_layer_subset, p$layers)
p$layers <- append(na_layer, p$layers)
p$layers <- append(base_layer, p$layers)
suppressMessages({
p <- p +
ggplot2::scale_x_continuous(limits = c(min(p$layers[[1]]$data$x),
max(p$layers[[1]]$data$x))) +
ggplot2::scale_y_continuous(limits = c(min(p$layers[[1]]$data$y),
max(p$layers[[1]]$data$y)))
})
}
if (isTRUE(plot_density_contour)){
data <- ggplot2::ggplot_build(p)
density_layer <- ggplot2::stat_density_2d(data = data$data[[1]],
mapping = ggplot2::aes(x = .data$x,
y = .data$y),
color = contour.color,
lineend = contour.lineend,
linejoin = contour.linejoin)
if (contour.position == "bottom"){
p$layers <- append(density_layer, p$layers)
} else if (contour.position == "top"){
p$layers <- append(p$layers, density_layer)
}
min_x <- min(data$data[[1]]$x) * (1 + contour_expand_axes)
max_x <- max(data$data[[1]]$x) * (1 + contour_expand_axes)
min_y <- min(data$data[[1]]$y) * (1 + contour_expand_axes)
max_y <- max(data$data[[1]]$y) * (1 + contour_expand_axes)
# Expand axes limits to allocate the new contours.
suppressMessages({
p <- p +
ggplot2::xlim(c(min_x, max_x)) +
ggplot2::ylim(c(min_y, max_y))
})
}
# Titles in split.by are centered by default.
hjust_use <- if(split_by_used){0.5} else {0}
# Add theme settings to all plots.
p <- p &
ggplot2::theme_minimal(base_size = font.size) &
ggplot2::theme(plot.title = ggplot2::element_text(face = plot.title.face, hjust = hjust_use),
plot.subtitle = ggplot2::element_text(face = plot.subtitle.face, hjust = 0),
plot.caption = ggplot2::element_text(face = plot.caption.face, hjust = 1),
plot.title.position = "plot",
plot.caption.position = "plot",
text = ggplot2::element_text(family = font.type),
legend.justification = "center",
legend.text = ggplot2::element_text(face = legend.text.face),
legend.title = if (legend.position != "none") {ggplot2::element_text(face = legend.title.face)} else {ggplot2::element_blank()},
legend.position = legend.position,
panel.grid = ggplot2::element_blank(),
plot.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0),
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"))
}
# Add plot title to the plots.
if (!is.null(plot.title)){
if (!(is.null(split.by))){
p <- p +
patchwork::plot_annotation(title = plot.title)
} else {
p <- p &
ggplot2::labs(title = plot.title)
}
}
# Add plot subtitle to the plots.
if (!is.null(plot.subtitle)){
if (!(is.null(split.by))){
p <- p +
patchwork::plot_annotation(subtitle = plot.subtitle)
} else {
p <- p +
ggplot2::labs(subtitle = plot.subtitle)
}
}
# Add plot caption to the plots.
if (!is.null(plot.caption)){
if (!(is.null(split.by))){
p <- p +
patchwork::plot_annotation(caption = plot.caption)
} else {
p <- p +
ggplot2::labs(caption = plot.caption)
}
}
if (base::isFALSE(plot.axes)){
p <- p &
ggplot2::theme(axis.title = ggplot2::element_blank(),
axis.text = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
axis.line = ggplot2::element_blank())
} else {
p <- p &
ggplot2::theme(axis.title = ggplot2::element_text(face = axis.title.face),
axis.text = ggplot2::element_text(face = axis.text.face),
axis.ticks = ggplot2::element_line(color = "black"),
axis.line = ggplot2::element_line(color = "black"))
}
# Add marginal plots.
if (not_highlighting_and_not_split_by & isTRUE(plot_marginal_distributions & base::isFALSE(plot_cell_borders))){
# Remove annoying warnings when violin is used as marginal distribution.
if (marginal.type == "violin"){
p <- suppressWarnings({ggExtra::ggMarginal(p = p,
groupColour = ifelse(isTRUE(marginal.group), TRUE, FALSE),
groupFill = ifelse(isTRUE(marginal.group), TRUE, FALSE),
type = marginal.type,
size = marginal.size)})
} else {
p <- ggExtra::ggMarginal(p = p,
groupColour = ifelse(isTRUE(marginal.group), TRUE, FALSE),
groupFill = ifelse(isTRUE(marginal.group), TRUE, FALSE),
type = marginal.type,
size = marginal.size)
}
# Transform back to ggplot2 object.
p <- ggplotify::as.ggplot(p)
# Fix for the plot backgrounds after applying ggMarginal.
p$theme$plot.background <- ggplot2::element_rect(fill = "white", color = "white")
p$theme$legend.background <- ggplot2::element_rect(fill = "white", color = "white")
p$theme$panel.background <- ggplot2::element_rect(fill = "white", color = "white")
} else if (isTRUE(plot_marginal_distributions)) {
stop(paste0(add_cross(),
crayon_body("Marginal distributions can not be used alongside when splitting by categories ("),
crayon_key("split.by"),
crayon_body("), highlighting cells ("),
crayon_key("cells.highlight/idents.highlight"),
crayon_body(") or plotting cell borders ("),
crayon_key("plot_cell_borders"),
crayon_body(").")), call. = FALSE)
}
# Return the final plot.
return(p)
}
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