Improve interactions grids with gridExtra
This commit is contained in:
@@ -6,6 +6,7 @@ suppressMessages({
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library("rlang")
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library("ggthemes")
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library("data.table")
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library("gridExtra")
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library("future")
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library("furrr")
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library("purrr")
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@@ -371,124 +372,128 @@ calculate_interaction_scores <- function(df, max_conc, bg_stats,
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interactions_joined = interactions_joined))
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}
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generate_and_save_plots <- function(out_dir, filename, plot_configs, grid_layout = NULL) {
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generate_and_save_plots <- function(out_dir, filename, plot_configs) {
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message("Generating ", filename, ".pdf and ", filename, ".html")
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# Prepare lists to collect plots
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static_plots <- list()
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plotly_plots <- list()
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# Iterate through the plot_configs (which contain both plots and grid_layout)
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for (config_group in plot_configs) {
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plot_list <- config_group$plots
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grid_nrow <- config_group$grid_layout$nrow
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grid_ncol <- config_group$grid_layout$ncol
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for (i in seq_along(plot_configs)) {
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config <- plot_configs[[i]]
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df <- config$df
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# Prepare lists to collect static and interactive plots
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static_plots <- list()
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plotly_plots <- list()
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# Create the base plot
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aes_mapping <- if (config$plot_type == "bar") {
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if (!is.null(config$color_var)) {
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aes(x = .data[[config$x_var]], fill = as.factor(.data[[config$color_var]]), color = as.factor(.data[[config$color_var]]))
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# Generate each individual plot based on the configuration
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for (i in seq_along(plot_list)) {
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config <- plot_list[[i]]
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df <- config$df
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# Create the base plot
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aes_mapping <- if (config$plot_type == "bar") {
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if (!is.null(config$color_var)) {
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aes(x = .data[[config$x_var]], fill = as.factor(.data[[config$color_var]]), color = as.factor(.data[[config$color_var]]))
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} else {
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aes(x = .data[[config$x_var]])
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}
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} else if (config$plot_type == "density") {
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if (!is.null(config$color_var)) {
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aes(x = .data[[config$x_var]], color = as.factor(.data[[config$color_var]]))
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} else {
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aes(x = .data[[config$x_var]])
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}
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} else {
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aes(x = .data[[config$x_var]])
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if (!is.null(config$color_var)) {
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aes(x = .data[[config$x_var]], y = .data[[config$y_var]], color = as.factor(.data[[config$color_var]]))
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} else {
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aes(x = .data[[config$x_var]], y = .data[[config$y_var]])
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}
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}
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} else if (config$plot_type == "density") {
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if (!is.null(config$color_var)) {
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aes(x = .data[[config$x_var]], color = as.factor(.data[[config$color_var]]))
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} else {
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aes(x = .data[[config$x_var]])
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plot <- ggplot(df, aes_mapping)
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# Apply theme_publication with legend_position from config
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legend_position <- if (!is.null(config$legend_position)) config$legend_position else "bottom"
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plot <- plot + theme_publication(legend_position = legend_position)
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# Use appropriate helper function based on plot type
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plot <- switch(config$plot_type,
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"scatter" = generate_scatter_plot(plot, config),
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"box" = generate_box_plot(plot, config),
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"density" = plot + geom_density(),
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"bar" = plot + geom_bar(),
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plot # default case if no type matches
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)
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# Add title and labels
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if (!is.null(config$title)) {
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plot <- plot + ggtitle(config$title)
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}
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} else {
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if (!is.null(config$color_var)) {
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aes(x = .data[[config$x_var]], y = .data[[config$y_var]], color = as.factor(.data[[config$color_var]]))
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} else {
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aes(x = .data[[config$x_var]], y = .data[[config$y_var]])
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if (!is.null(config$x_label)) {
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plot <- plot + xlab(config$x_label)
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}
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if (!is.null(config$y_label)) {
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plot <- plot + ylab(config$y_label)
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}
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# Add cartesian coordinates if specified
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if (!is.null(config$coord_cartesian)) {
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plot <- plot + coord_cartesian(ylim = config$coord_cartesian)
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}
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# Apply scale_color_discrete(guide = FALSE) when color_var is NULL
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if (is.null(config$color_var)) {
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plot <- plot + scale_color_discrete(guide = "none")
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}
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# Add interactive tooltips for plotly
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tooltip_vars <- c()
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if (config$plot_type == "scatter") {
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if (!is.null(config$delta_bg_point) && config$delta_bg_point) {
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tooltip_vars <- c(tooltip_vars, "OrfRep", "Gene", "delta_bg")
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} else if (!is.null(config$gene_point) && config$gene_point) {
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tooltip_vars <- c(tooltip_vars, "OrfRep", "Gene")
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} else if (!is.null(config$y_var) && !is.null(config$x_var)) {
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tooltip_vars <- c(config$x_var, config$y_var)
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}
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}
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# Convert to plotly object and suppress warnings here
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plotly_plot <- suppressWarnings({
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if (length(tooltip_vars) > 0) {
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ggplotly(plot, tooltip = tooltip_vars)
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} else {
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ggplotly(plot, tooltip = "none")
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}
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})
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# Adjust legend position if specified
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if (!is.null(config$legend_position) && config$legend_position == "bottom") {
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plotly_plot <- plotly_plot %>% layout(legend = list(orientation = "h"))
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}
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# Add plots to lists
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static_plots[[i]] <- plot
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plotly_plots[[i]] <- plotly_plot
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}
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plot <- ggplot(df, aes_mapping)
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# Save static PDF plot(s) for the current grid
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pdf(file.path(out_dir, paste0(filename, ".pdf")), width = 16, height = 9)
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grid.arrange(grobs = static_plots, ncol = grid_ncol, nrow = grid_nrow)
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dev.off()
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# Apply theme_publication with legend_position from config
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legend_position <- if (!is.null(config$legend_position)) config$legend_position else "bottom"
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plot <- plot + theme_publication(legend_position = legend_position)
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# Use appropriate helper function based on plot type
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plot <- switch(config$plot_type,
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"scatter" = generate_scatter_plot(plot, config),
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"box" = generate_box_plot(plot, config),
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"density" = plot + geom_density(),
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"bar" = plot + geom_bar(),
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plot # default case if no type matches
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# Combine and save interactive HTML plot(s)
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combined_plot <- subplot(
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plotly_plots,
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nrows = grid_nrow,
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ncols = grid_ncol,
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margin = 0.05
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)
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# Add title and labels
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if (!is.null(config$title)) {
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plot <- plot + ggtitle(config$title)
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}
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if (!is.null(config$x_label)) {
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plot <- plot + xlab(config$x_label)
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}
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if (!is.null(config$y_label)) {
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plot <- plot + ylab(config$y_label)
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}
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# Add cartesian coordinates if specified
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if (!is.null(config$coord_cartesian)) {
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plot <- plot + coord_cartesian(ylim = config$coord_cartesian)
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}
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# Apply scale_color_discrete(guide = FALSE) when color_var is NULL
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if (is.null(config$color_var)) {
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plot <- plot + scale_color_discrete(guide = "none")
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}
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# Add interactive tooltips for plotly
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tooltip_vars <- c()
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if (config$plot_type == "scatter") {
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if (!is.null(config$delta_bg_point) && config$delta_bg_point) {
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tooltip_vars <- c(tooltip_vars, "OrfRep", "Gene", "delta_bg")
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} else if (!is.null(config$gene_point) && config$gene_point) {
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tooltip_vars <- c(tooltip_vars, "OrfRep", "Gene")
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} else if (!is.null(config$y_var) && !is.null(config$x_var)) {
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tooltip_vars <- c(config$x_var, config$y_var)
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}
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}
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# Convert to plotly object and suppress warnings here
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plotly_plot <- suppressWarnings({
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if (length(tooltip_vars) > 0) {
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ggplotly(plot, tooltip = tooltip_vars)
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} else {
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ggplotly(plot, tooltip = "none")
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}
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})
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# Adjust legend position if specified
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if (!is.null(config$legend_position) && config$legend_position == "bottom") {
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plotly_plot <- plotly_plot %>% layout(legend = list(orientation = "h"))
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}
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# Add plots to lists
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static_plots[[i]] <- plot
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plotly_plots[[i]] <- plotly_plot
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# Save combined HTML plot(s)
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saveWidget(combined_plot, file = file.path(out_dir, paste0(filename, ".html")), selfcontained = TRUE)
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}
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# Save static PDF plot(s)
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pdf(file.path(out_dir, paste0(filename, ".pdf")), width = 14, height = 9)
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lapply(static_plots, print)
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dev.off()
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# Combine and save interactive HTML plot(s)
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combined_plot <- subplot(
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plotly_plots,
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nrows = if (!is.null(grid_layout) && !is.null(grid_layout$nrow)) {
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grid_layout$nrow
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} else {
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# Calculate nrow based on the length of plotly_plots
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ceiling(length(plotly_plots) / ifelse(!is.null(grid_layout) && !is.null(grid_layout$ncol), grid_layout$ncol, 1))
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},
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margin = 0.05
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)
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# Save combined html plot(s)
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saveWidget(combined_plot, file = file.path(out_dir, paste0(filename, ".html")), selfcontained = TRUE)
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}
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generate_scatter_plot <- function(plot, config) {
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@@ -686,102 +691,76 @@ generate_plate_analysis_plot_configs <- function(variables, stages = c("before",
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return(plots)
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}
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generate_interaction_plot_configs <- function(df, limits_map = NULL) {
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# Default limits_map if not provided
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generate_interaction_plot_configs <- function(df, limits_map = NULL, stats_df = NULL) {
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if (is.null(limits_map)) {
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limits_map <- list(
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L = c(-65, 65),
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K = c(-65, 65),
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r = c(-0.65, 0.65),
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AUC = c(-6500, 6500)
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L = c(0, 130),
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K = c(-20, 160),
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r = c(0, 1),
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AUC = c(0, 12500)
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)
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}
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# Filter data
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df_filtered <- df
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# Ensure proper grouping by OrfRep, Gene, and num
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df_filtered <- df %>%
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filter(
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!is.na(L) & L >= limits_map$L[1] & L <= limits_map$L[2],
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!is.na(K) & K >= limits_map$K[1] & K <= limits_map$K[2],
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!is.na(r) & r >= limits_map$r[1] & r <= limits_map$r[2],
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!is.na(AUC) & AUC >= limits_map$AUC[1] & AUC <= limits_map$AUC[2]
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) %>%
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group_by(OrfRep, Gene, num) # Group by OrfRep, Gene, and num
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scatter_configs <- list()
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box_configs <- list()
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# Generate scatter and box plots for each variable (L, K, r, AUC)
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for (var in names(limits_map)) {
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df_filtered <- df_filtered %>%
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filter(!is.na(!!sym(var)) &
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!!sym(var) >= limits_map[[var]][1] &
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!!sym(var) <= limits_map[[var]][2])
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}
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configs <- list()
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for (var in names(limits_map)) {
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y_range <- limits_map[[var]]
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# Calculate annotation positions
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y_min <- min(y_range)
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y_max <- max(y_range)
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y_span <- y_max - y_min
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annotation_positions <- list(
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ZShift = y_max - 0.1 * y_span,
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lm_ZScore = y_max - 0.2 * y_span,
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NG = y_min + 0.2 * y_span,
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DB = y_min + 0.1 * y_span,
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SM = y_min + 0.05 * y_span
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)
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# Prepare linear model line
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lm_line <- list(
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intercept = df_filtered[[paste0("lm_intercept_", var)]],
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slope = df_filtered[[paste0("lm_slope_", var)]]
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)
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# Calculate x-axis position for annotations
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num_levels <- length(levels(df_filtered$conc_num_factor))
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x_pos <- (1 + num_levels) / 2
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# Generate annotations
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annotations <- lapply(names(annotation_positions), function(annotation_name) {
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label <- switch(annotation_name,
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ZShift = paste("ZShift =", round(df_filtered[[paste0("Z_Shift_", var)]], 2)),
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lm_ZScore = paste("lm ZScore =", round(df_filtered[[paste0("Z_lm_", var)]], 2)),
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NG = paste("NG =", df_filtered$NG),
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DB = paste("DB =", df_filtered$DB),
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SM = paste("SM =", df_filtered$SM),
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NULL
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)
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if (!is.null(label)) {
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list(x = x_pos, y = annotation_positions[[annotation_name]], label = label)
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} else {
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NULL
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}
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})
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annotations <- Filter(Negate(is.null), annotations)
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# Shared plot settings
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plot_settings <- list(
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scatter_configs[[length(scatter_configs) + 1]] <- list(
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df = df_filtered,
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x_var = "conc_num_factor",
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y_var = var,
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ylim_vals = y_range,
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annotations = annotations,
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lm_line = lm_line,
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x_breaks = levels(df_filtered$conc_num_factor),
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x_labels = levels(df_filtered$conc_num_factor),
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x_label = unique(df_filtered$Drug[1]),
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coord_cartesian = y_range,
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)
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# Scatter plot config
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configs[[length(configs) + 1]] <- modifyList(plot_settings, list(
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x_var = "conc_num", # X-axis variable
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y_var = var, # Y-axis variable (Delta_L, Delta_K, Delta_r, Delta_AUC)
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plot_type = "scatter",
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title = sprintf("%s %s", df_filtered$OrfRep[1], df_filtered$Gene[1]),
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error_bar = TRUE,
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position = "jitter",
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size = 1
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))
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# Box plot config
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configs[[length(configs) + 1]] <- modifyList(plot_settings, list(
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title = sprintf("Scatter RF for %s with SD", var),
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coord_cartesian = limits_map[[var]], # Set limits for Y-axis
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annotations = list(
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list(x = -0.25, y = 10, label = "NG"),
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list(x = -0.25, y = 5, label = "DB"),
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list(x = -0.25, y = 0, label = "SM")
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),
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grid_layout = list(ncol = 4, nrow = 3)
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)
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box_configs[[length(box_configs) + 1]] <- list(
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df = df_filtered,
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x_var = "conc_num", # X-axis variable
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y_var = var, # Y-axis variable (Delta_L, Delta_K, Delta_r, Delta_AUC)
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plot_type = "box",
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title = sprintf("%s %s (box plot)", df_filtered$OrfRep[1], df_filtered$Gene[1]),
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error_bar = FALSE
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))
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title = sprintf("Boxplot RF for %s with SD", var),
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coord_cartesian = limits_map[[var]],
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grid_layout = list(ncol = 4, nrow = 3)
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)
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}
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# Combine scatter and box plots into grids
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configs <- list(
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list(
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grid_layout = list(nrow = 2, ncol = 2), # Scatter plots in a 2x2 grid (for the 8 plots)
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plots = scatter_configs[1:4]
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),
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list(
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grid_layout = list(nrow = 2, ncol = 2), # Box plots in a 2x2 grid (for the 8 plots)
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plots = box_configs
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),
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list(
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grid_layout = list(nrow = 3, ncol = 4), # Delta_ plots in a 3x4 grid
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plots = scatter_configs
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),
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list(
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grid_layout = list(nrow = 3, ncol = 4), # Delta_ box plots in a 3x4 grid
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plots = box_configs
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)
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)
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return(configs)
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}
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@@ -864,7 +843,8 @@ generate_rank_plot_configs <- function(df, variables, is_lm = FALSE, adjust = FA
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size = 0.1,
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y_label = y_label,
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x_label = "Rank",
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legend_position = "none"
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legend_position = "none",
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grid_layout = list(ncol = 3, nrow = 2)
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)
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# Non-Annotated Plot Configuration
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@@ -884,7 +864,8 @@ generate_rank_plot_configs <- function(df, variables, is_lm = FALSE, adjust = FA
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size = 0.1,
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y_label = y_label,
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x_label = "Rank",
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legend_position = "none"
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legend_position = "none",
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grid_layout = list(ncol = 3, nrow = 2)
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)
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}
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}
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@@ -1006,7 +987,8 @@ generate_correlation_plot_configs <- function(df) {
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fill = NA, color = "grey20", alpha = 0.1
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)
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),
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cyan_points = TRUE
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cyan_points = TRUE,
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grid_layout = list(ncol = 2, nrow = 2)
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)
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configs[[length(configs) + 1]] <- config
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@@ -1258,9 +1240,9 @@ main <- function() {
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)
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# Generating quality control plots in parallel
|
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furrr::future_map(plot_configs, function(config) {
|
||||
generate_and_save_plots(config$out_dir, config$filename, config$plot_configs)
|
||||
}, .options = furrr_options(seed = TRUE))
|
||||
# furrr::future_map(plot_configs, function(config) {
|
||||
# generate_and_save_plots(config$out_dir, config$filename, config$plot_configs)
|
||||
# }, .options = furrr_options(seed = TRUE))
|
||||
|
||||
# Process background strains
|
||||
bg_strains <- c("YDL227C")
|
||||
@@ -1345,11 +1327,11 @@ main <- function() {
|
||||
# Create interaction plots
|
||||
message("Generating reference interaction plots")
|
||||
reference_plot_configs <- generate_interaction_plot_configs(zscore_interactions_reference_joined)
|
||||
generate_and_save_plots(out_dir, "interaction_plots_reference", reference_plot_configs, grid_layout = list(ncol = 4, nrow = 3))
|
||||
generate_and_save_plots(out_dir, "interaction_plots_reference", reference_plot_configs)
|
||||
|
||||
message("Generating deletion interaction plots")
|
||||
deletion_plot_configs <- generate_interaction_plot_configs(zscore_interactions_joined)
|
||||
generate_and_save_plots(out_dir, "interaction_plots", deletion_plot_configs, grid_layout = list(ncol = 4, nrow = 3))
|
||||
generate_and_save_plots(out_dir, "interaction_plots", deletion_plot_configs)
|
||||
|
||||
# Define conditions for enhancers and suppressors
|
||||
# TODO Add to study config?
|
||||
@@ -1408,7 +1390,7 @@ main <- function() {
|
||||
adjust = TRUE
|
||||
)
|
||||
generate_and_save_plots(out_dir = out_dir, filename = "rank_plots",
|
||||
plot_configs = rank_plot_configs, grid_layout = list(ncol = 3, nrow = 2))
|
||||
plot_configs = rank_plot_configs)
|
||||
|
||||
message("Generating ranked linear model plots")
|
||||
rank_lm_plot_configs <- generate_rank_plot_configs(
|
||||
@@ -1418,7 +1400,7 @@ main <- function() {
|
||||
adjust = TRUE
|
||||
)
|
||||
generate_and_save_plots(out_dir = out_dir, filename = "rank_plots_lm",
|
||||
plot_configs = rank_lm_plot_configs, grid_layout = list(ncol = 3, nrow = 2))
|
||||
plot_configs = rank_lm_plot_configs)
|
||||
|
||||
message("Filtering and reranking plots")
|
||||
interaction_threshold <- 2 # TODO add to study config?
|
||||
@@ -1454,8 +1436,7 @@ main <- function() {
|
||||
generate_and_save_plots(
|
||||
out_dir = out_dir,
|
||||
filename = "RankPlots_na_rm",
|
||||
plot_configs = rank_plot_filtered_configs,
|
||||
grid_layout = list(ncol = 3, nrow = 2))
|
||||
plot_configs = rank_plot_filtered_configs)
|
||||
|
||||
message("Generating filtered ranked linear model plots")
|
||||
rank_plot_lm_filtered_configs <- generate_rank_plot_configs(
|
||||
@@ -1468,8 +1449,7 @@ main <- function() {
|
||||
generate_and_save_plots(
|
||||
out_dir = out_dir,
|
||||
filename = "rank_plots_lm_na_rm",
|
||||
plot_configs = rank_plot_lm_filtered_configs,
|
||||
grid_layout = list(ncol = 3, nrow = 2))
|
||||
plot_configs = rank_plot_lm_filtered_configs)
|
||||
|
||||
message("Generating correlation curve parameter pair plots")
|
||||
correlation_plot_configs <- generate_correlation_plot_configs(zscore_interactions_filtered)
|
||||
@@ -1477,7 +1457,7 @@ main <- function() {
|
||||
out_dir = out_dir,
|
||||
filename = "correlation_cpps",
|
||||
plot_configs = correlation_plot_configs,
|
||||
grid_layout = list(ncol = 2, nrow = 2))
|
||||
)
|
||||
})
|
||||
})
|
||||
}
|
||||
|
||||
@@ -1260,7 +1260,7 @@ qhtcp() {
|
||||
# done
|
||||
|
||||
# Run R interactions script on all studies
|
||||
calculate_interaction_zscores \
|
||||
calculate_interaction_zscores; exit \
|
||||
&& join_interaction_zscores \
|
||||
&& remc \
|
||||
&& gtf \
|
||||
|
||||
Reference in New Issue
Block a user