Use htmltools to combine html widgets into single file
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@@ -406,14 +406,6 @@ generate_and_save_plots <- function(out_dir, filename, plot_configs) {
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config <- plot_configs$plots[[i]]
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df <- config$df
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message("Processing plot ", i, ": ", config$title)
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message("Plot type: ", config$plot_type)
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if (is.null(df)) {
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message("Dataframe for plot ", i, " is NULL.")
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next
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}
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# Define aes_mapping, ensuring y_var is only used when it's not NULL
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aes_mapping <- switch(config$plot_type,
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"bar" = if (!is.null(config$color_var)) {
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@@ -490,14 +482,16 @@ generate_and_save_plots <- function(out_dir, filename, plot_configs) {
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dev.off()
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# Save individual interactive HTML plots
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for (i in seq_along(plotly_plots)) {
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html_file <- file.path(out_dir, paste0(filename, "_plot_", i, ".html"))
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message("Saving HTML plot ", i, ": ", html_file)
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htmlwidgets::saveWidget(plotly_plots[[i]], file = html_file, selfcontained = TRUE)
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}
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# Save combined HTML plot
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out_html_file <- file.path(out_dir, paste0(filename, ".html"))
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message("Saving combined HTML file: ", out_html_file)
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htmltools::save_html(
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htmltools::tagList(plotly_plots),
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file = out_html_file
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)
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}
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generate_scatter_plot <- function(plot, config) {
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# Define the points
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@@ -804,136 +798,75 @@ generate_interaction_plot_configs <- function(df, limits_map = NULL, plot_type =
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generate_rank_plot_configs <- function(df, variables, is_lm = FALSE, adjust = FALSE, overlap_color = FALSE) {
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sd_bands <- c(1, 2, 3)
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avg_zscore_cols <- paste0("Avg_Zscore_", variables)
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z_lm_cols <- paste0("Z_lm_", variables)
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configs <- list()
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# Adjust values if necessary
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if (adjust) {
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df <- df %>%
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mutate(across(all_of(avg_zscore_cols), ~ ifelse(is.na(.), 0.001, .))) %>%
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mutate(across(all_of(z_lm_cols), ~ ifelse(is.na(.), 0.001, .)))
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# Adjust (if necessary) and rank columns
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for (variable in variables) {
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if (adjust) {
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df[[paste0("Avg_Zscore_", variable)]] <- ifelse(is.na(df[[paste0("Avg_Zscore_", variable)]]), 0.001, df[[paste0("Avg_Zscore_", variable)]])
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df[[paste0("Z_lm_", variable)]] <- ifelse(is.na(df[[paste0("Z_lm_", variable)]]), 0.001, df[[paste0("Z_lm_", variable)]])
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}
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df[[paste0("Rank_", variable)]] <- rank(df[[paste0("Avg_Zscore_", variable)]], na.last = "keep")
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df[[paste0("Rank_lm_", variable)]] <- rank(df[[paste0("Z_lm_", variable)]], na.last = "keep")
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}
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# Calculate rank columns for Avg_Zscore and Z_lm columns
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df_ranked <- df %>%
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mutate(across(all_of(avg_zscore_cols), rank, .names = "Rank_{col}")) %>%
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mutate(across(all_of(z_lm_cols), rank, .names = "Rank_lm_{col}"))
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# Helper function to create a plot configuration
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create_plot_config <- function(variable, rank_var, zscore_var, y_label, sd_band, with_annotations = TRUE) {
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num_enhancers <- sum(df[[zscore_var]] >= sd_band, na.rm = TRUE)
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num_suppressors <- sum(df[[zscore_var]] <= -sd_band, na.rm = TRUE)
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# Default plot config
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plot_config <- list(
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df = df,
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x_var = rank_var,
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y_var = zscore_var,
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plot_type = "scatter",
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title = paste(y_label, "vs. Rank for", variable, "above", sd_band),
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sd_band = sd_band,
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fill_positive = "#542788",
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fill_negative = "orange",
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alpha_positive = 0.3,
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alpha_negative = 0.3,
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annotations = NULL,
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shape = 3,
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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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)
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if (with_annotations) {
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# Add specific annotations for plots with annotations
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plot_config$annotations <- list(
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list(
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x = median(df[[rank_var]], na.rm = TRUE),
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y = max(df[[zscore_var]], na.rm = TRUE) * 0.9,
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label = paste("Deletion Enhancers =", num_enhancers)
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),
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list(
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x = median(df[[rank_var]], na.rm = TRUE),
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y = min(df[[zscore_var]], na.rm = TRUE) * 0.9,
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label = paste("Deletion Suppressors =", num_suppressors)
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)
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)
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}
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# Generate plots for SD-based L and K variables
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for (variable in c("L", "K")) {
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return(plot_config)
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}
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# Generate plots for each variable
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for (variable in variables) {
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rank_var <- if (is_lm) paste0("Rank_lm_", variable) else paste0("Rank_", variable)
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zscore_var <- if (is_lm) paste0("Z_lm_", variable) else paste0("Avg_Zscore_", variable)
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y_label <- if (is_lm) paste("Int Z score", variable) else paste("Avg Z score", variable)
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# Loop through SD bands
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for (sd_band in sd_bands) {
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num_enhancers <- sum(df_ranked[[zscore_var]] >= sd_band, na.rm = TRUE)
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num_suppressors <- sum(df_ranked[[zscore_var]] <= -sd_band, na.rm = TRUE)
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# Plot with annotations
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configs[[length(configs) + 1]] <- list(
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df = df_ranked,
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x_var = rank_var,
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y_var = zscore_var,
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plot_type = "scatter",
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title = paste(y_label, "vs. Rank for", variable, "above", sd_band, "SD"),
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sd_band = sd_band,
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fill_positive = "#542788",
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fill_negative = "orange",
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alpha_positive = 0.3,
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alpha_negative = 0.3,
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annotations = list(
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list(
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x = median(df_ranked[[rank_var]], na.rm = TRUE),
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y = max(df_ranked[[zscore_var]], na.rm = TRUE) * 0.9,
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label = paste("Deletion Enhancers =", num_enhancers)
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),
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list(
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x = median(df_ranked[[rank_var]], na.rm = TRUE),
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y = min(df_ranked[[zscore_var]], na.rm = TRUE) * 0.9,
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label = paste("Deletion Suppressors =", num_suppressors)
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)
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),
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shape = 3,
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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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)
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# Plot without annotations
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configs[[length(configs) + 1]] <- list(
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df = df_ranked,
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x_var = rank_var,
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y_var = zscore_var,
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plot_type = "scatter",
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title = paste(y_label, "vs. Rank for", variable, "above", sd_band, "SD No Annotations"),
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sd_band = sd_band,
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fill_positive = "#542788",
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fill_negative = "orange",
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alpha_positive = 0.3,
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alpha_negative = 0.3,
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annotations = NULL,
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shape = 3,
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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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)
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}
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}
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# Generate Avg ZScore and Rank Avg ZScore plots for each variable
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for (variable in variables) {
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for (plot_type in c("Avg Zscore vs lm", "Rank Avg Zscore vs lm")) {
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title <- paste(plot_type, variable)
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# Define specific variables based on plot type
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x_var <- if (plot_type == "Avg Zscore vs lm") paste0("Avg_Zscore_", variable) else paste0("Rank_", variable)
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y_var <- if (plot_type == "Avg Zscore vs lm") paste0("Z_lm_", variable) else paste0("Rank_lm_", variable)
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# Fit the linear model
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lm_model <- lm(as.formula(paste(y_var, "~", x_var)), data = df_ranked)
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intercept <- coef(lm_model)[1]
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slope <- coef(lm_model)[2]
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r_squared <- summary(lm_model)$r.squared
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annotations <- list(
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list(
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x = mean(range(df_ranked[[x_var]], na.rm = TRUE)),
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y = mean(range(df_ranked[[y_var]], na.rm = TRUE)),
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label = paste("R-squared =", round(r_squared, 2)),
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hjust = 0.5,
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vjust = 1,
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size = 5
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)
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)
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rectangles <- if (plot_type == "Avg Zscore vs lm") {
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list(list(xmin = -2, xmax = 2, ymin = -2, ymax = 2, fill = NA, color = "grey20", alpha = 0.1))
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} else {
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NULL
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}
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configs[[length(configs) + 1]] <- list(
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df = df_ranked,
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x_var = x_var,
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y_var = y_var,
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plot_type = "scatter",
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title = title,
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annotations = annotations,
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shape = 3,
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size = 0.25,
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smooth = TRUE,
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smooth_color = "black",
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lm_line = list(intercept = intercept, slope = slope),
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legend_position = "right",
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color_var = if (overlap_color) "Overlap" else NULL,
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x_label = x_var,
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y_label = y_var,
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rectangles = rectangles
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)
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# Create plot with annotations
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configs[[length(configs) + 1]] <- create_plot_config(variable, rank_var, zscore_var, y_label, sd_band, with_annotations = TRUE)
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# Create plot without annotations
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configs[[length(configs) + 1]] <- create_plot_config(variable, rank_var, zscore_var, y_label, sd_band, with_annotations = FALSE)
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}
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}
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