Nothing
R/volcanoplot.R
Defines functions VolcanoPlot VolcanoPlotAtomic
Documented in VolcanoPlot VolcanoPlotAtomic
#' Atomic volcano plot
#'
#' @inheritParams common_args
#' @param ytrans A function to transform the y-axis values.
#' @param color_by A character vector of column names to color the points by.
#' If NULL, the points will be filled by the x and y cutoff value.
#' @param color_name A character string to name the legend of color.
#' @param flip_negatives A logical value to flip the y-axis for negative x values.
#' @param trim A numeric vector of length 2 to trim the x-axis values.
#' The values must be in the range from 0 to 1, which works as quantile to trim the x-axis values.
#' For example, c(0.01, 0.99) will trim the 1% and 99% quantile of the x-axis values.
#' If the values are less then 1% or greater than 99% quantile, the values will be set to the 1% or 99% quantile.
#' @param xlim A numeric vector of length 2 to set the x-axis limits.
#' @param x_cutoff A numeric value to set the x-axis cutoff.
#' Both negative and positive of this value will be used.
#' @param y_cutoff A numeric value to set the y-axis cutoff.
#' Note that the y-axis cutoff will be transformed by `ytrans`.
#' So you should provide the original value.
#' @param x_cutoff_name A character string to name the x-axis cutoff.
#' If "none", the legend for the x-axis cutoff will not be shown.
#' @param y_cutoff_name A character string to name the y-axis cutoff.
#' If "none", the legend for the y-axis cutoff will not be shown.
#' @param x_cutoff_color A character string to color the x-axis cutoff line.
#' @param y_cutoff_color A character string to color the y-axis cutoff line.
#' @param x_cutoff_linetype A character string to set the x-axis cutoff line type.
#' @param y_cutoff_linetype A character string to set the y-axis cutoff line type.
#' @param x_cutoff_linewidth A numeric value to set the x-axis cutoff line size.
#' @param y_cutoff_linewidth A numeric value to set the y-axis cutoff line size.
#' @param pt_size A numeric value to set the point size.
#' @param pt_alpha A numeric value to set the point transparency.
#' @param nlabel A numeric value to set the number of labels to show.
#' The points will be ordered by the distance to the origin. Top `nlabel` points will be labeled.
#' @param labels A character vector of row names or indexes to label the points.
#' @param label_size A numeric value to set the label size.
#' @param label_fg A character string to set the label color.
#' @param label_bg A character string to set the label background color.
#' @param label_bg_r A numeric value specifying the radius of the background of the label.
#' @param highlight A character vector of row names or indexes to highlight the points.
#' @param highlight_color A character string to set the highlight color.
#' @param highlight_size A numeric value to set the highlight size.
#' @param highlight_alpha A numeric value to set the highlight transparency.
#' @param highlight_stroke A numeric value to set the highlight stroke size.
#'
#' @return A ggplot object
#' @keywords internal
#' @importFrom dplyr %>% case_when mutate arrange row_number group_by ungroup desc filter
VolcanoPlotAtomic <- function(
data, x, y, ytrans = function(n) -log10(n), color_by = NULL, color_name = NULL,
flip_negatives = FALSE, x_cutoff = NULL, y_cutoff = 0.05, trim = c(0, 1), xlim = NULL,
x_cutoff_name = NULL, y_cutoff_name = NULL, x_cutoff_color = "red2", y_cutoff_color = "blue2",
x_cutoff_linetype = "dashed", y_cutoff_linetype = "dashed", x_cutoff_linewidth = 0.5, y_cutoff_linewidth = 0.5,
pt_size = 2, pt_alpha = 0.5, nlabel = 5, labels = NULL, label_size = 3, label_fg = "black", label_bg = "white",
label_bg_r = 0.1, highlight = NULL, highlight_color = "red", highlight_size = 2, highlight_alpha = 1,
highlight_stroke = 0.5, facet_by = NULL, facet_scales = "fixed", facet_ncol = NULL, facet_nrow = NULL, facet_byrow = TRUE,
theme = "theme_this", theme_args = list(), palette = "Spectral", palcolor = NULL,
title = NULL, subtitle = NULL, xlab = NULL, ylab = NULL,
aspect.ratio = 1, legend.position = "right", legend.direction = "vertical", seed = 8525,
...
) {
ggplot <- if (getOption("plotthis.gglogger.enabled", FALSE)) {
gglogger::ggplot
} else {
ggplot2::ggplot
}
stopifnot(
"[VolcanoPlot] 'trim' must be a numeric vector of length 2 and both values must be in the range [0, 1]." =
length(trim) == 2 && all(trim >= 0 & trim <= 1)
)
stopifnot("[VolcanoPlot] 'xlim' must be a numeric vector of length 2." = is.null(xlim) || length(xlim) == 2)
trim <- sort(trim)
x <- check_columns(data, x)
y <- check_columns(data, y)
color_by <- check_columns(data, color_by)
facet_by <- check_columns(data, facet_by, force_factor = TRUE, allow_multi = TRUE)
data[[y]] <- ytrans(data[[y]])
x_cutoff <- x_cutoff %||% 0
y_cutoff <- ytrans(y_cutoff)
if (!is.null(y_cutoff)) {
data <- data %>% mutate(
.category = factor(
case_when(
!!sym(x) > x_cutoff & !!sym(y) > y_cutoff ~ "sig_pos_x",
!!sym(x) < -x_cutoff & !!sym(y) > y_cutoff ~ "sig_neg_x",
TRUE ~ "insig"
),
levels = c("sig_neg_x", "insig", "sig_pos_x")
)
)
} else {
data <- data %>% mutate(
.category = factor(
case_when(
!!sym(x) > x_cutoff ~ "sig_pos_x",
!!sym(x) < -x_cutoff ~ "sig_neg_x",
TRUE ~ "insig"
),
levels = c("sig_neg_x", "insig", "sig_pos_x")
)
)
}
if (is.null(color_by)) {
color_by <- ".category"
color_type <- "discrete"
} else if (is.character(data[[color_by]]) || is.factor(data[[color_by]])) {
color_type <- "discrete"
} else {
color_type <- "continuous"
}
if (flip_negatives) {
data[data[[x]] < 0, y] <- -data[data[[x]] < 0, y]
}
data$.label <- rownames(data)
data$.show_label <- FALSE
x_upper <- quantile(data[[x]][is.finite(data[[x]])], c(trim[2], 1))
x_lower <- quantile(data[[x]][is.finite(data[[x]])], c(trim[1], 0))
x_upper <- ifelse(x_upper[1] > 0, x_upper[1], x_upper[2])
x_lower <- ifelse(x_lower[1] < 0, x_lower[1], x_lower[2])
if (x_upper > 0 & x_lower < 0) {
value_range <- min(abs(c(x_upper, x_lower)), na.rm = TRUE)
x_upper <- value_range
x_lower <- -value_range
}
data$.outlier <- data[[x]] > x_upper | data[[x]] < x_lower
data[[x]][data[[x]] > x_upper] <- x_upper
data[[x]][data[[x]] < x_lower] <- x_lower
if (!is.null(labels)) {
data[labels, ".show_label"] <- TRUE
} else {
# calculate the distance to the origin
data$.distance <- sqrt(data[[x]]^2 + data[[y]]^2)
if (!is.null(facet_by)) {
data <- data %>% group_by(!!!syms(facet_by), sign(data[[x]])) %>%
arrange(desc(!!sym(".distance"))) %>%
mutate(.show_label = row_number() <= nlabel) %>%
ungroup()
} else {
data <- data %>% group_by(sign(data[[x]])) %>%
arrange(desc(!!sym(".distance"))) %>%
mutate(.show_label = row_number() <= nlabel) %>%
ungroup()
}
}
data <- data %>% mutate(.show_label = !!sym(".show_label") & !!sym(".category") != "insig") %>%
as.data.frame()
rownames(data) <- data$.label
# x_nudge is not an aesthetic, we can't specify it separately for negative and positive values
# so we plot the points in two layers
# one for negative values and one for positive values
# and set the x_nudge for each layer
pos_data <- data[data[[x]] >= 0, , drop = FALSE]
neg_data <- data[data[[x]] < 0, , drop = FALSE]
outlier_data <- data[data$.outlier, , drop = FALSE]
# x_nudges will be the same for all facets
pos_x_nudge <- -diff(range(pos_data[[x]])) * 0.05
neg_x_nudge <- diff(range(neg_data[[x]])) * 0.05
jitter <- position_jitter(width = 0.2, height = 0.2, seed = seed)
p <- ggplot(mapping = aes(x = !!sym(x), y = !!sym(y), color = !!sym(color_by))) +
geom_point(data = pos_data, size = pt_size, alpha = pt_alpha) +
geom_point(data = neg_data, size = pt_size, alpha = pt_alpha) +
geom_point(data = outlier_data, size = pt_size, alpha = pt_alpha, position = jitter)
if (color_type == "discrete") {
colors <- palette_this(levels(data[[color_by]]), palette = palette, palcolor = palcolor)
if (is.null(palcolor)) {
colors['insig'] <- "grey"
}
p <- p + scale_color_manual(values = colors, guide = "none")
} else {
p <- p + scale_color_gradientn(
colors = palette_this(palette = palette, palcolor = palcolor),
values = scales::rescale(unique(c(
min(c(unlist(data[[color_by]]), 0), na.rm = TRUE), 0,
max(unlist(data[[color_by]]), na.rm = TRUE)))),
guide = guide_colorbar(frame.colour = "black", ticks.colour = "black", title.hjust = 0, order = 1)
)
}
if (!is.null(highlight)) {
p <- p + geom_point(
data = data[highlight, , drop = FALSE] %>% filter(!!sym(".outlier") == FALSE),
color = highlight_color, size = highlight_size, alpha = highlight_alpha, stroke = highlight_stroke
) + geom_point(
data = data[highlight, , drop = FALSE] %>% filter(!!sym(".outlier")),
color = highlight_color, size = highlight_size, alpha = highlight_alpha, stroke = highlight_stroke, position = jitter
)
}
if (!is.null(x_cutoff) && x_cutoff != 0) {
if (identical(x_cutoff_name, "none")) {
guide <- guide_none()
} else {
guide <- guide_legend(override.aes = list(alpha = 0.8, size = 5), order = 2,
theme = ggplot2::theme(legend.margin = margin(0, 0, -10, 4.5)))
}
vline_df <- data.frame(xintercept = c(-x_cutoff, x_cutoff))
if (!is.null(facet_by)) {
vline_df <- expand_grid(vline_df, data[, facet_by, drop = FALSE] %>% distinct())
}
p <- p +
new_scale_color() +
geom_vline(
data = vline_df,
mapping = aes(
xintercept = !!sym("xintercept"),
color = x_cutoff_name %||% paste0(x, " = +/-", scales::number(x_cutoff, accuracy = 0.01))),
alpha = 0.4, linetype = x_cutoff_linetype, size = x_cutoff_linewidth,
) +
scale_color_manual(name = NULL, values = x_cutoff_color, guide = guide)
}
if (!is.null(y_cutoff)) {
if (isTRUE(flip_negatives)) {
yintercept <- c(-y_cutoff, y_cutoff)
} else {
yintercept <- y_cutoff
}
if (identical(y_cutoff_name, "none")) {
guide <- guide_none()
} else {
guide <- guide_legend(override.aes = list(alpha = 0.8, size = 5), order = 3)
}
hline_df <- data.frame(yintercept = yintercept)
if (!is.null(facet_by)) {
hline_df <- expand_grid(hline_df, data[, facet_by, drop = FALSE] %>% distinct())
}
p <- p +
new_scale_color() +
geom_hline(
data = hline_df,
mapping = aes(yintercept = !!sym("yintercept"),
color = y_cutoff_name %||% paste0(ylab %||% y, " = ", scales::number(y_cutoff, accuracy = 0.01))),
alpha = 0.4, linetype = y_cutoff_linetype, size = y_cutoff_linewidth
) +
scale_color_manual(
name = NULL,
values = y_cutoff_color,
guide = guide
)
}
if (isTRUE(flip_negatives)) {
p <- p +
geom_hline(yintercept = 0, color = "black", linetype = 1) +
scale_y_continuous(labels = abs)
}
if (!is.null(xlim)) {
p <- p + ggplot2::xlim(xlim)
}
p <- p +
geom_vline(xintercept = 0, color = "grey80", linetype = 2) +
geom_text_repel(
data = pos_data[pos_data$.show_label, , drop = FALSE], aes(label = !!sym(".label")), nudge_x = pos_x_nudge, color = label_fg,
bg.color = label_bg, bg.r = label_bg_r, size = label_size, min.segment.length = 0, segment.color = "grey40",
max.overlaps = 100
) +
geom_text_repel(
data = neg_data[neg_data$.show_label, , drop = FALSE], aes(label = !!sym(".label")), nudge_x = neg_x_nudge, color = label_fg,
bg.color = label_bg, bg.r = label_bg_r, size = label_size, min.segment.length = 0, segment.color = "grey40",
max.overlaps = 100
) +
labs(title = title, subtitle = subtitle, x = xlab %||% x, y = ylab %||% y) +
coord_cartesian(clip = "off")
p <- p +
do.call(theme, theme_args) +
ggplot2::theme(
aspect.ratio = aspect.ratio,
legend.position = legend.position,
legend.direction = legend.direction
)
height <- 5
width <- 5
if (!identical(legend.position, "none")) {
if (legend.position %in% c("right", "left")) {
width <- width + 1
} else if (legend.direction == "horizontal") {
height <- height + 1
} else {
width <- width + 2
}
}
attr(p, "height") <- height
attr(p, "width") <- width
facet_plot(p, facet_by, facet_scales, facet_nrow, facet_ncol, facet_byrow,
legend.position = legend.position, legend.direction = legend.direction)
}
#' Volcano plot
#'
#' @description A volcano plot is a type of scatter plot that shows statistical significance (usually on the y-axis) versus magnitude of change (usually on the x-axis).
#' @inheritParams common_args
#' @inheritParams VolcanoPlotAtomic
#' @return A list of ggplot objects or a wrap_plots object
#' @export
#' @examples
#' \donttest{
#' set.seed(8525)
#' # Obtained by Seurat::FindMakers for the first cluster of pbmc_small
#' data <- data.frame(
#' avg_log2FC = c(
#' -3.69, -4.10, -2.68, -3.51, -3.09, -2.52, -3.53, -3.35, -2.82, -2.71, -3.16, -2.24,
#' -5.62, -3.10, -3.42, -2.72, -3.23, -3.25, -4.68, 3.67, -2.66, 4.79, -2.99, 10.14,
#' -1.78, -2.67, -2.26, -2.59, -3.39, 5.36, 4.56, 4.62, -2.94, -9.47, -9.12, -1.63,
#' -2.77, 3.31, -1.53, -3.89, -4.21, 4.72, -2.98, -2.29, -1.41, -9.48, -4.30, 3.01,
#' -1.19, -4.83, -1.35, -1.68, -1.63, -2.70, 3.86, 3.81, 7.23, -1.45, -0.92, -2.45,
#' 3.91, -4.45, -9.33, 3.56, 2.27, -1.60, -1.15, 11.40, -9.77, -8.32, 2.61, -1.25,
#' -1.72, 10.61, 11.34, 10.02, 2.78, -3.48, -1.98, 5.86, 5.57, 4.57, 9.75, 9.97,
#' 10.90, 9.19, 2.93, 5.10, -1.52, -3.93, -1.95, -2.46, -0.64, 4.60, -1.82, -0.80,
#' 9.34, 7.51, 6.45, 5.23, 4.41, 3.60, -1.94, -1.15),
#' p_val_adj = c(
#' 3.82e-09, 1.52e-07, 1.79e-07, 4.68e-07, 4.83e-07, 6.26e-07, 2.61e-06, 1.33e-05,
#' 1.79e-05, 3.71e-05, 5.21e-05, 5.36e-05, 5.83e-05, 6.66e-05, 8.22e-05, 2.89e-04,
#' 3.00e-04, 4.94e-04, 7.62e-04, 8.93e-04, 9.55e-04, 9.61e-04, 1.12e-03, 1.47e-03,
#' 1.66e-03, 1.95e-03, 2.06e-03, 3.01e-03, 3.26e-03, 4.35e-03, 4.85e-03, 5.12e-03,
#' 5.40e-03, 7.18e-03, 7.18e-03, 1.04e-02, 1.24e-02, 1.90e-02, 1.94e-02, 1.97e-02,
#' 2.09e-02, 2.13e-02, 2.25e-02, 2.61e-02, 3.18e-02, 3.27e-02, 3.69e-02, 3.80e-02,
#' 4.95e-02, 5.73e-02, 5.77e-02, 6.10e-02, 6.22e-02, 6.31e-02, 6.72e-02, 9.23e-02,
#' 9.85e-02, 1.06e-01, 1.07e-01, 1.11e-01, 1.31e-01, 1.38e-01, 1.40e-01, 1.43e-01,
#' 2.00e-01, 2.39e-01, 2.49e-01, 2.57e-01, 2.86e-01, 2.86e-01, 2.98e-01, 3.32e-01,
#' 4.15e-01, 4.91e-01, 4.91e-01, 4.91e-01, 5.97e-01, 7.11e-01, 7.59e-01, 8.38e-01,
#' 9.20e-01, 9.20e-01, 9.29e-01, 9.29e-01, 9.29e-01, 9.29e-01, 9.34e-01, 9.68e-01,
#' 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00,
#' 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00, 1.00e+00),
#' gene = c(
#' "HLA-DPB1", "LYZ", "HLA-DRA", "TYMP", "HLA-DPA1", "HLA-DRB1", "CST3", "HLA-DQB1",
#' "HLA-DRB5", "LST1", "HLA-DQA1", "AIF1", "S100A8", "IFITM3", "HLA-DMB", "FCGRT",
#' "SERPINA1", "IFI30", "S100A9", "CCL5", "GRN", "LCK", "HLA-DMA", "MS4A6A", "CTSS",
#' "CFP", "FCN1", "BID", "CFD", "CD3D", "CD7", "CD3E", "LGALS2", "CD14", "SMCO4",
#' "LINC00936", "HCK", "CTSW", "LGALS1", "HLA-DQA2", "LRRC25", "GZMM", "RNF130",
#' "LGALS3", "S100A11", "C5AR1", "IL1B", "GZMA", "FCER1G", "MPEG1", "TYROBP", "TSPO",
#' "GSTP1", "CTSB", "IL32", "CD247", "GNLY", "COTL1", "NFKBIA", "NUP214", "LAMP1",
#' "FPR1", "CLEC10A", "CST7", "PRF1", "BLVRA", "PSAP", "GZMH", "EAF2", "ASGR1",
#' "RARRES3", "SAT1", "LY86", "GP9", "TUBB1", "NGFRAP1", "XBP1", "SCO2", "RGS2", "GZMB",
#' "HIST1H2AC", "KLRD1", "PGRMC1", "AKR1C3", "PTGDR", "IL2RB", "GYPC", "CCL4", "CD68",
#' "FCER1A", "CD79B", "MS4A7", "CARD16", "ACAP1", "CD79A", "ANXA2", "TMEM40", "PF4",
#' "GNG11", "CLU", "CD9", "FGFBP2", "TNFRSF1B", "IFI6"),
#' pct_diff = c(
#' -0.752, -0.457, -0.460, -0.671, -0.626, -0.701, -0.502, -0.619, -0.623, -0.598,
#' -0.566, -0.626, -0.543, -0.566, -0.541, -0.542, -0.515, -0.489, -0.444, 0.428,
#' -0.517, 0.461, -0.491, -0.410, -0.480, -0.491, -0.521, -0.491, -0.438, 0.411,
#' 0.411, 0.409, -0.438, -0.359, -0.359, -0.440, -0.386, 0.385, -0.332, -0.361, -0.361,
#' 0.364, -0.387, -0.415, -0.454, -0.308, -0.335, 0.364, -0.454, -0.309, -0.379, -0.427,
#' -0.377, -0.389, 0.335, 0.315, 0.313, -0.284, -0.502, -0.309, 0.313, -0.284, -0.256,
#' 0.309, 0.313, -0.364, -0.406, 0.244, -0.231, -0.231, 0.281, -0.311, -0.312, 0.220,
#' 0.220, 0.220, 0.261, -0.232, -0.367, 0.240, 0.218, 0.218, 0.195, 0.195, 0.195, 0.195,
#' 0.262, 0.218, -0.288, -0.207, -0.290, -0.233, -0.367, 0.217, -0.233, -0.403, 0.171,
#' 0.194, 0.194, 0.194, 0.194, 0.213, -0.235, -0.292),
#' group = sample(LETTERS[1:2], 104, replace = TRUE)
#' )
#' rownames(data) <- data$gene
#'
#' VolcanoPlot(data, x = "avg_log2FC", y = "p_val_adj", color_by = "pct_diff",
#' y_cutoff_name = "-log10(0.05)")
#' VolcanoPlot(data, x = "avg_log2FC", y = "p_val_adj", y_cutoff_name = "none",
#' flip_negatives = TRUE)
#' VolcanoPlot(data, x = "avg_log2FC", y = "p_val_adj", y_cutoff_name = "none",
#' flip_negatives = TRUE, facet_by = "group")
#' VolcanoPlot(data, x = "avg_log2FC", y = "p_val_adj", y_cutoff_name = "none",
#' flip_negatives = TRUE, split_by = "group")
#' VolcanoPlot(data, x = "avg_log2FC", y = "p_val_adj", y_cutoff_name = "none",
#' highlight = c("ANXA2", "TMEM40", "PF4", "GNG11", "CLU", "CD9", "FGFBP2",
#' "TNFRSF1B", "IFI6"))
#' VolcanoPlot(data, x = "avg_log2FC", y = "p_val_adj", color_by = "pct_diff",
#' y_cutoff_name = "-log10(0.05)", split_by = "group",
#' palette = c(A = "Set1", B = "Dark2"))
#' }
VolcanoPlot <- function(
data, x, y, ytrans = function(n) -log10(n), color_by = NULL, color_name = NULL, xlim = NULL,
flip_negatives = FALSE, x_cutoff = NULL, y_cutoff = 0.05, split_by = NULL, split_by_sep = "_",
x_cutoff_name = NULL, y_cutoff_name = NULL, x_cutoff_color = "red2", y_cutoff_color = "blue2",
x_cutoff_linetype = "dashed", y_cutoff_linetype = "dashed", x_cutoff_linewidth = 0.5, y_cutoff_linewidth = 0.5,
pt_size = 2, pt_alpha = 0.5, nlabel = 5, labels = NULL, label_size = 3, label_fg = "black", label_bg = "white",
label_bg_r = 0.1, highlight = NULL, highlight_color = "red", highlight_size = 2, highlight_alpha = 1,
highlight_stroke = 0.5, trim = c(0, 1),
facet_by = NULL, facet_scales = "fixed", facet_ncol = NULL, facet_nrow = NULL, facet_byrow = TRUE,
theme = "theme_this", theme_args = list(), palette = "Spectral", palcolor = NULL,
title = NULL, subtitle = NULL, xlab = NULL, ylab = NULL,
aspect.ratio = 1, legend.position = "right", legend.direction = "vertical", seed = 8525,
combine = TRUE, nrow = NULL, ncol = NULL, byrow = TRUE,
axes = NULL, axis_titles = axes, guides = NULL, design = NULL, ...
) {
validate_common_args(seed, facet_by = facet_by)
theme <- process_theme(theme)
split_by <- check_columns(data, split_by, force_factor = TRUE, allow_multi = TRUE,
concat_multi = TRUE, concat_sep = split_by_sep)
if (!is.null(split_by)) {
datas <- split(data, data[[split_by]])
# keep the order of levels
datas <- datas[levels(data[[split_by]])]
} else {
datas <- list(data)
names(datas) <- "..."
}
palette <- check_palette(palette, names(datas))
palcolor <- check_palcolor(palcolor, names(datas))
legend.direction <- check_legend(legend.direction, names(datas), "legend.direction")
legend.position <- check_legend(legend.position, names(datas), "legend.position")
plots <- lapply(
names(datas), function(nm) {
default_title <- if (length(datas) == 1 && identical(nm, "...")) NULL else nm
if (is.function(title)) {
title <- title(default_title)
} else {
title <- title %||% default_title
}
VolcanoPlotAtomic(datas[[nm]],
x = x, y = y, ytrans = ytrans, color_by = color_by, color_name = color_name,
flip_negatives = flip_negatives, x_cutoff = x_cutoff, y_cutoff = y_cutoff, trim = trim, xlim = xlim,
x_cutoff_name = x_cutoff_name, y_cutoff_name = y_cutoff_name, x_cutoff_color = x_cutoff_color, y_cutoff_color = y_cutoff_color,
x_cutoff_linetype = x_cutoff_linetype, y_cutoff_linetype = y_cutoff_linetype, x_cutoff_linewidth = x_cutoff_linewidth, y_cutoff_linewidth = y_cutoff_linewidth,
pt_size = pt_size, pt_alpha = pt_alpha, nlabel = nlabel, labels = labels, label_size = label_size, label_fg = label_fg, label_bg = label_bg,
label_bg_r = label_bg_r, highlight = highlight, highlight_color = highlight_color, highlight_size = highlight_size, highlight_alpha = highlight_alpha,
highlight_stroke = highlight_stroke,
facet_by = facet_by, facet_scales = facet_scales, facet_ncol = facet_ncol, facet_nrow = facet_nrow, facet_byrow = facet_byrow,
theme = theme, theme_args = theme_args, palette = palette[[nm]], palcolor = palcolor[[nm]],
title = title, subtitle = subtitle, xlab = xlab, ylab = ylab,
aspect.ratio = aspect.ratio, legend.position = legend.position[[nm]], legend.direction = legend.direction[[nm]], seed = seed, ...
)
}
)
combine_plots(plots, combine = combine, nrow = nrow, ncol = ncol, byrow = byrow,
axes = axes, axis_titles = axis_titles, guides = guides, design = design)
}
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