Improve generate_and_save_plots()

workflow/apps/r/calculate_interaction_zscores5.R

@@ -143,13 +143,10 @@ update_gene_names <- function(df, sgd_gene_list) {
   
   # Create a named vector for mapping ORF to GeneName
   gene_map <- setNames(genes$V5, genes$V4)
-  
   # Vectorized match to find the GeneName from gene_map
   mapped_genes <- gene_map[df$ORF]
-  
   # Replace NAs in mapped_genes with original Gene names (preserves existing Gene names if ORF is not found)
   updated_genes <- ifelse(is.na(mapped_genes) | df$OrfRep == "YDL227C", df$Gene, mapped_genes)
-  
   # Ensure Gene is not left blank or incorrectly updated to "OCT1"
   df <- df %>%
     mutate(Gene = ifelse(updated_genes == "" | updated_genes == "OCT1", OrfRep, updated_genes))
@@ -313,104 +310,102 @@ calculate_interaction_scores <- function(df, max_conc, variables, group_vars = c
   return(list(zscores_calculations = interaction_scores_all, zscores_interactions = interaction_scores))
 }
 
-generate_plot <- function(df, x_var, y_var = NULL, plot_type = "scatter", color_var = "conc_num",
+generate_and_save_plots <- function(output_dir, file_name, plot_configs) {
-  title = "", x_label = NULL, y_label = NULL, ylim_vals = NULL, annotations = NULL) {
 
-  plot <- ggplot(df, aes(x = !!sym(x_var), color = as.factor(!!sym(color_var))))
+  `%||%` <- function(a, b) if (!is.null(a)) a else b
 
-  if (!is.null(y_var)) {
+  # Generalized plot generation
-    plot <- plot + aes(y = !!sym(y_var))
+  plots <- lapply(plot_configs, function(config) {
     
-    # Add scatter points with summary stats if `y_var` is present
+    # Use the dataframe from the plot configuration
-    y_mean_col <- paste0("mean_", y_var)
+    df <- config$df
-    y_sd_col <- paste0("sd_", y_var)
 
-    plot <- plot + geom_point(shape = 3, size = 0.2) +
+    # Initialize the basic ggplot
-      geom_errorbar(aes(
+    plot <- ggplot(df, aes(x = if (config$plot_type == "box") as.factor(!!sym(config$x_var)) else !!sym(config$x_var),
-        ymin = !!sym(y_mean_col) - !!sym(y_sd_col),
+      color = as.factor(!!sym(config$color_var))))
-        ymax = !!sym(y_mean_col) + !!sym(y_sd_col)),
-        width = 0.1) +
-      geom_point(aes(y = !!sym(y_mean_col)), size = 0.6)
-  }
 
-  # Add the specified plot type
+    # Handle specific y_var cases, like "delta_bg"
-  plot <- switch(plot_type,
+    if (!is.null(config$y_var)) {
-    "box" = plot + geom_boxplot(),
+      plot <- plot + aes(y = !!sym(config$y_var))
-    "density" = plot + geom_density(),
-    "bar" = plot + geom_bar(stat = "identity"),
-    plot + geom_point() + geom_smooth(method = "lm", se = FALSE)  # Default is scatter
-  )
 
-  if (!is.null(ylim_vals)) {
+      y_mean_col <- paste0("mean_", config$y_var)
-    plot <- plot + coord_cartesian(ylim = ylim_vals)
+      y_sd_col <- paste0("sd_", config$y_var)
-  }
 
-  plot <- plot + ggtitle(title) + theme_publication()
+      # Special case for "delta_bg" to add jitter
-  
+      if (config$y_var == "delta_bg" && config$plot_type == "scatter") {
-  if (!is.null(x_label)) plot <- plot + xlab(x_label)
+        plot <- plot + geom_point(shape = 3, size = 0.2, position = "jitter") +
-  if (!is.null(y_label)) plot <- plot + ylab(y_label)
+          geom_errorbar(aes(
-
+            ymin = !!sym(y_mean_col) - !!sym(y_sd_col),
-  if (!is.null(annotations)) {
+            ymax = !!sym(y_mean_col) + !!sym(y_sd_col)),
-    for (annotation in annotations) {
+            width = 0.1) +
-      plot <- plot + annotate("text",
+          geom_point(aes(y = !!sym(y_mean_col)), size = 0.6)
-        x = annotation$x,
+      } else if (config$error_bar %||% FALSE) {
-        y = annotation$y,
+        plot <- plot +
-        label = annotation$label)
+          geom_point(shape = 3, size = 0.2) +
+          geom_errorbar(aes(
+            ymin = !!sym(y_mean_col) - !!sym(y_sd_col),
+            ymax = !!sym(y_mean_col) + !!sym(y_sd_col)),
+            width = 0.1) +
+          geom_point(aes(y = !!sym(y_mean_col)), size = 0.6) +
+          stat_summary(aes(
+            ymin = !!sym(y_mean_col) - !!sym(y_sd_col),
+            ymax = !!sym(y_mean_col) + !!sym(y_sd_col)),
+            fun.data = "identity", geom = "errorbar", width = 0.1) +
+          stat_summary(aes(y = !!sym(y_mean_col)),
+            fun.data = "identity", geom = "point", size = 0.6)
+      }
     }
-  }
 
-  return(plot)
+    # Switch plot type (scatter, box, density, bar)
-}
+    plot <- switch(config$plot_type,
-
+      "box" = plot + geom_boxplot(),
-generate_and_save_plots <- function(df, output_dir, file_prefix, plot_configs) {
+      "density" = plot + geom_density(),
-  plots <- list()
+      "bar" = plot + geom_bar(stat = "identity"),
-
+      plot + geom_point() + geom_smooth(method = "lm", se = FALSE)  # Default is scatter
-  if (nrow(df) == 0) {
-    message("The dataframe is empty, skipping plots")
-    return()
-  }
-
-  message("Generating plots for dataframe")
-
-  for (config in plot_configs) {
-    plot <- generate_plot(
-      df = df,
-      x_var = config$x_var,
-      y_var = config$y_var,
-      plot_type = config$plot_type,
-      title = config$title,
-      ylim_vals = config$ylim_vals,
-      annotations = config$annotations
     )
 
-    plots[[paste0(config$y_var, "_", config$plot_type)]] <- plot
+    # Apply y-axis limits if provided
-  }
+    if (!is.null(config$ylim_vals)) {
+      plot <- plot + coord_cartesian(ylim = config$ylim_vals)
+    }
 
-  # Save plots to PDF and HTML
+    # Add title and publication theme with custom legend position
-  save_plots(file_prefix, plots, output_dir)
+    legend_position <- config$legend_position %||% "bottom"  # Default to bottom if not specified
-}
+    plot <- plot + ggtitle(config$title) + theme_publication(legend_position = legend_position)
 
-# Standardized saving of plots
+    # Add x and y axis labels if provided
-save_plots <- function(file_name, plot_list, output_dir) {
+    if (!is.null(config$x_label)) plot <- plot + xlab(config$x_label)
+    if (!is.null(config$y_label)) plot <- plot + ylab(config$y_label)
+
+    # Add custom annotations if provided
+    if (!is.null(config$annotations)) {
+      for (annotation in config$annotations) {
+        plot <- plot + annotate("text",
+          x = annotation$x,
+          y = annotation$y,
+          label = annotation$label)
+      }
+    }
+
+    return(plot)
+  })
+
+  # Save plots to PDF
   pdf(file.path(output_dir, paste0(file_name, ".pdf")), width = 14, height = 9)
-  lapply(plot_list, print)
+  lapply(plots, print)
   dev.off()
 
-  lapply(names(plot_list), function(plot_name) {
+  # Convert plots to plotly and combine them using subplot
-    pgg <- tryCatch({
+  plotly_plots <- lapply(plots, function(plot) {
-      suppressWarnings(ggplotly(plot_list[[plot_name]]) %>%
+    suppressWarnings(ggplotly(plot) %>%
-        layout(legend = list(orientation = "h")))
+      layout(legend = list(orientation = "h")))
-    }, error = function(e) {
-      message("Error generating plot: ", plot_name)
-      return(NULL)
-    })
-
-    if (!is.null(pgg)) {
-      saveWidget(pgg,
-        file = file.path(output_dir, paste0(file_name, "_", plot_name, ".html")),
-        selfcontained = TRUE)
-    }
   })
+  
+  # Combine all plotly plots into a single interactive layout using subplot
+  combined_plot <- subplot(plotly_plots, nrows = length(plotly_plots), margin = 0.05)
+  
+  # Save the combined HTML file
+  saveWidget(combined_plot, file = file.path(output_dir, paste0(file_name, ".html")), selfcontained = TRUE)
 }
 
 interaction_plot_configs <- function(df, variables) {
@@ -493,42 +488,6 @@ adjust_missing_and_rank <- function(df, variables) {
   return(df)
 }
 
-generate_plots <- function(df, x_var, y_vars, plot_type, color_var = "conc_num", title_prefix = "",
-  x_label = NULL, y_label = NULL, ylim_vals = NULL, output_dir, file_prefix = "plot") {
-  plot_list <- list()
-  
-  # Iterate over each y variable and generate the corresponding plot
-  for (var in y_vars) {
-    plot <- ggplot(df, aes(x = !!sym(x_var), y = !!sym(var), color = as.factor(!!sym(color_var)))) +
-      ggtitle(paste(title_prefix, var)) +
-      theme_publication()
-    
-    if (plot_type == "scatter") {
-      plot <- plot +
-        geom_point() +
-        geom_smooth(method = "lm", formula = y ~ x, se = FALSE)
-      
-      if (!is.null(ylim_vals)) {
-        plot <- plot + coord_cartesian(ylim = ylim_vals)
-      }
-    } else if (plot_type == "box") {
-      plot <- plot + geom_boxplot()
-    } else if (plot_type == "density") {
-      plot <- plot + geom_density()
-    } else if (plot_type == "bar") {
-      plot <- plot + geom_bar()
-    }
-    
-    if (!is.null(x_label)) plot <- plot + xlab(x_label)
-    if (!is.null(y_label)) plot <- plot + ylab(y_label)
-    
-    plot_list[[var]] <- plot
-  }
-  
-  # Save plots to PDF and HTML
-  save_plots(file_prefix, plot_list, output_dir)
-}
-
 main <- function() {
   lapply(names(args$experiments), function(exp_name) {
     exp <- args$experiments[[exp_name]]
@@ -540,7 +499,7 @@ main <- function() {
     dir.create(out_dir_qc, recursive = TRUE, showWarnings = FALSE)
     
     # Load and process data
-    df <- load_and_process_data(args$easy_results_file, exp_sd)
+    df <- load_and_process_data(args$easy_results_file, sd = exp_sd)
     df <- update_gene_names(df, args$sgd_gene_list)
     
     max_conc <- max(df$conc_num_factor)
@@ -583,40 +542,223 @@ main <- function() {
         df_na %>% filter(if_all(c(L), is.finite))
       }
 
-    # Define the plot configurations for each QC step
+    # Plot configurations
-    qc_plot_configs <- list(
+    # Each list corresponds to a group of plots in the same file
-      list(x_var = "L", y_var = "K", plot_type = "scatter", title = "Raw L vs K before QC", ylim_vals = NULL),
+    raw_l_vs_k_plots <- list(
-      list(x_var = "delta_bg", y_var = NULL, plot_type = "density", title = "Density plot for Delta Background", ylim_vals = NULL),
+      list(df = df, x_var = "L", y_var = "K", plot_type = "scatter",
-      list(x_var = "as.factor(delta_bg)", y_var = NULL, plot_type = "bar", title = "Bar plot for Delta Background", ylim_vals = NULL)
+        title = "Raw L vs K before QC",
+        color_var = "conc_num",
+        legend_position = "right")
     )
 
+    above_threshold_plots <- list(
+      list(df = df_above_tolerance, x_var = "L", y_var = "K", plot_type = "scatter",
+        title = paste("Raw L vs K for strains above delta background threshold of", df_above_tolerance$delta_bg_tolerance[[1]], "or above"),
+        color_var = "conc_num",
+        annotations = list(
+          list(
+            x = L_half_median,
+            y = K_half_median,
+            label = paste("Strains above delta background tolerance =", nrow(df_above_tolerance))
+          )
+        ),
+        error_bar = FALSE,
+        legend_position = "right"
+      )
+    )
+
+    frequency_delta_bg_plots <- list(
+      list(df = df, x_var = "delta_bg", y_var = NULL, plot_type = "density",
+        title = "Density plot for Delta Background by Conc All Data",
+        color_var = "conc_num",
+        x_label = "Delta Background",
+        y_label = "Density",
+        error_bar = FALSE,
+        legend_position = "right"
+      ),
+      list(df = df, x_var = "delta_bg", y_var = NULL, plot_type = "bar",
+        title = "Bar plot for Delta Background by Conc All Data",
+        color_var = "conc_num",
+        x_label = "Delta Background",
+        y_label = "Count",
+        error_bar = FALSE,
+        legend_position = "right"
+      )
+    )
+
+    plate_analysis_plots <- list()
+    for (plot_type in c("scatter", "box")) {
+      variables <- c("L", "K", "r", "AUC", "delta_bg")
+      for (var in variables) {
+        for (stage in c("before", "after")) {
+          if (stage == "before") {
+            df_plot <- df
+          } else {
+            df_plot <- df_na # TODO use df_na_filtered if necessary
+          }
+          
+          # Set error_bar = TRUE only for scatter plots
+          error_bar <- ifelse(plot_type == "scatter", TRUE, FALSE)
+          
+          # Create the plot configuration
+          plot_config <- list(
+            df = df_plot,
+            x_var = "scan",
+            y_var = var,
+            plot_type = plot_type,
+            title = paste("Plate analysis by Drug Conc for", var, stage, "quality control"),
+            error_bar = error_bar,
+            color_var = "conc_num"
+          )
+          plate_analysis_plots <- append(plate_analysis_plots, list(plot_config))
+        }
+      }
+    }
+
+    plate_analysis_no_zero_plots <- list()
+      for (plot_type in c("scatter", "box")) {
+        variables <- c("L", "K", "r", "AUC", "delta_bg")
+        for (var in variables) {
+            
+          # Set error_bar = TRUE only for scatter plots
+          error_bar <- ifelse(plot_type == "scatter", TRUE, FALSE)
+          
+          # Create the plot configuration
+          plot_config <- list(
+            df = df_no_zeros,
+            x_var = "scan",
+            y_var = var,
+            plot_type = plot_type,
+            title = paste("Plate analysis by Drug Conc for", var, "after quality control"),
+            error_bar = error_bar,
+            color_var = "conc_num"
+          )
+          plate_analysis_plots <- append(plate_analysis_plots, list(plot_config))
+        }
+      }
+
+
+
+
+
+
+    delta_bg_plot_configs <- list(
+      list(x_var = "delta_bg", y_var = NULL, plot_type = "density",
+        title = paste("Raw L vs K for strains above delta background threshold of", delta_bg_tolerance, "or above"),
+        ylim_vals = NULL,
+        annotate("text", x = L_half_median, y = K_half_median,
+           label = paste("Strains above delta background tolerance = ", nrow(df_above_tolerance)))
+        )
+
+
+
+    )
+
+    before_qc_configs <- list(
+      list(x_var = "scan", y_var = "delta_bg", plot_type = "scatter",
+        title = "Plate analysis by Drug Conc for Delta Background before QC",
+        error_bar = TRUE, color_var = "conc_num"),
+      list(x_var = "scan", y_var = "delta_bg", plot_type = "box",
+        title = "Plate analysis by Drug Conc for Delta Background before QC",
+        error_bar = FALSE, color_var = "conc_num")
+    )
+
+
+
+
+
+
+
+
+    above_delta_bg_tolerance <- list(
+
+
+
+
+
+
+
+
+    )
+
+
+
+
+    # Print quality control graphs before removing data due to contamination and
+    # adjusting missing data to max theoretical values
+    before_qc_plot_configs <- list(
+      # Plate analysis is a quality check to identify plate effects containing anomalies
+
+    )
+
+      # list(x_var = "delta_bg", y_var = NULL, plot_type = "density",
+      #   title = "Density plot for Delta Background",
+      #   ylim_vals = NULL),
+      # list(x_var = "as.factor(delta_bg)", y_var = NULL, plot_type = "bar",
+      #   title = "Bar plot for Delta Background",
+      #   ylim_vals = NULL)
+
     above_tolerance_plot_configs <- list(
-      list(x_var = "L", y_var = "K", plot_type = "scatter", title = "L vs K for Rows Above Delta Background Threshold", ylim_vals = NULL)
+      list(x_var = "L", y_var = "K", plot_type = "scatter",
+        title = "Raw L vs K for strains above delta background threshold", ylim_vals = NULL)
     )
 
     after_qc_plot_configs <- list(
-      list(x_var = "L", y_var = "K", plot_type = "scatter", title = "L vs K After QC Filtering", ylim_vals = NULL)
+      list(x_var = "L", y_var = "K", plot_type = "scatter",
+        title = "L vs K After QC Filtering", ylim_vals = NULL)
     )
 
     no_zeros_plot_configs <- list(
-      list(x_var = "scan", y_var = "L", plot_type = "scatter", title = "L vs Scan for Non-Zero L Values"),
+      list(x_var = "scan", y_var = "L", plot_type = "scatter",
-      list(x_var = "scan", y_var = "K", plot_type = "scatter", title = "K vs Scan for Non-Zero L Values"),
+        title = "Plate analysis by Drug Conc for L after quality control",
-      list(x_var = "scan", y_var = "r", plot_type = "scatter", title = "r vs Scan for Non-Zero L Values"),
+        file_name = "Plate_Analysis_L_afterQC_Z", error_bar = TRUE, color_var = "conc_num"),
-      list(x_var = "scan", y_var = "AUC", plot_type = "scatter", title = "AUC vs Scan for Non-Zero L Values"),
+      list(x_var = "scan", y_var = "K", plot_type = "scatter",
-      list(x_var = "scan", y_var = "delta_bg", plot_type = "scatter", title = "Delta background vs Scan for Non-Zero L Values"),
+        title = "Plate analysis by Drug Conc for K after quality control",
-      list(x_var = "as.factor(scan)", y_var = "L", plot_type = "box", title = "L vs Scan for Non-Zero L Values"),
+        file_name = "Plate_Analysis_K_afterQC_Z", error_bar = TRUE, color_var = "conc_num"),
-      list(x_var = "as.factor(scan)", y_var = "K", plot_type = "box", title = "K vs Scan for Non-Zero L Values"),
+      list(x_var = "scan", y_var = "r", plot_type = "scatter",
-      list(x_var = "as.factor(scan)", y_var = "r", plot_type = "box", title = "r vs Scan for Non-Zero L Values"),
+        title = "Plate analysis by Drug Conc for r after quality control",
-      list(x_var = "as.factor(scan)", y_var = "AUC", plot_type = "box", title = "AUC vs Scan for Non-Zero L Values"),
+        file_name = "Plate_Analysis_r_afterQC_Z", error_bar = TRUE, color_var = "conc_num"),
-      list(x_var = "as.factor(scan)", y_var = "delta_bg", plot_type = "box", title = "Delta background vs Scan for Non-Zero L Values")
+      list(x_var = "scan", y_var = "AUC", plot_type = "scatter",
+        title = "Plate analysis by Drug Conc for AUC after quality control",
+        file_name = "Plate_Analysis_AUC_afterQC_Z", error_bar = TRUE, color_var = "conc_num"),
+      list(x_var = "scan", y_var = "delta_bg", plot_type = "scatter",
+        title = "Plate analysis by Drug Conc for Delta_Backgrd after quality control",
+        file_name = "Plate_Analysis_Delta_Backgrd_afterQC_Z", error_bar = TRUE, color_var = "conc_num"),
+      
+      # Box plots
+      list(x_var = "as.factor(scan)", y_var = "L", plot_type = "box",
+        title = "Plate analysis by Drug Conc for L after quality control",
+        file_name = "Plate_Analysis_L_Box_afterQC_Z"),
+      list(x_var = "as.factor(scan)", y_var = "K", plot_type = "box",
+        title = "Plate analysis by Drug Conc for K after quality control",
+        file_name = "Plate_Analysis_K_Box_afterQC_Z"),
+      list(x_var = "as.factor(scan)", y_var = "r", plot_type = "box",
+        title = "Plate analysis by Drug Conc for r after quality control",
+        file_name = "Plate_Analysis_r_Box_afterQC_Z"),
+      list(x_var = "as.factor(scan)", y_var = "AUC", plot_type = "box",
+        title = "Plate analysis by Drug Conc for AUC after quality control",
+        file_name = "Plate_Analysis_AUC_Box_afterQC_Z"),
+      list(x_var = "as.factor(scan)", y_var = "delta_bg", plot_type = "box",
+        title = "Plate analysis by Drug Conc for Delta_Backgrd after quality control",
+        file_name = "Plate_Analysis_Delta_Backgrd_Box_afterQC_Z")
     )
 
+
     # Generate and save plots for each QC step
     message("Generating QC plots")
-    generate_and_save_plots(df, out_dir_qc, "Before_QC", qc_plot_configs)
+    generate_and_save_plots(out_dir_qc, "L_vs_K_before_QC", raw_l_vs_k_plots)
-    generate_and_save_plots(df_above_tolerance, out_dir_qc, "Above_Tolerance", above_tolerance_plot_configs)
+    generate_and_save_plots(out_dir_qc, "L_vs_K_above_threshold", above_threshold_plots)
-    generate_and_save_plots(df_na_filtered, out_dir_qc, "After_QC", after_qc_plot_configs)
+    generate_and_save_plots(out_dir_qc, "frequency_delta_background", frequency_delta_bg_plots)
-    generate_and_save_plots(df_no_zeros, out_dir_qc, "No_Zeros", no_zeros_plot_configs)
+    generate_and_save_plots(out_dir_qc, "plate_analysis", plate_analysis_plots)
+    
+
+
+
+    generate_and_save_plots(df, out_dir_qc, "raw_L_vs_K_before_QC.pdf", delta_bg_plots)
+    generate_and_save_plots(df, out_dir_qc, "plate_analysis", before_qc_plot_configs)
+    generate_and_save_plots(df_above_tolerance, out_dir_qc, above_tolerance_plot_configs)
+    generate_and_save_plots(df_na_filtered, out_dir_qc, after_qc_plot_configs)
+    generate_and_save_plots(df_no_zeros, out_dir_qc, "plate_analysis_no_zeros", no_zeros_plot_configs)
 
     # Clean up
     rm(df, df_above_tolerance, df_no_zeros)
@@ -713,9 +855,9 @@ main <- function() {
 
       # Create interaction plots
       deletion_plot_configs <- interaction_plot_configs(df_reference, variables)
-      generate_and_save_plots(zscores_calculations, out_dir, "RF_InteractionPlots", deletion_plot_configs)
+      generate_and_save_plots(zscores_calculations, out_dir, deletion_plot_configs)
       deletion_plot_configs <- interaction_plot_configs(df_deletion, variables)
-      generate_and_save_plots(zscores_calculations, out_dir, "InteractionPlots", deletion_plot_configs)
+      generate_and_save_plots(zscores_calculations, out_dir, deletion_plot_configs)
 
       # Define conditions for enhancers and suppressors
       # TODO Add to study config file?
@@ -766,14 +908,6 @@ main <- function() {
       write.csv(suppressors_lm_K,
         file = file.path(out_dir, "ZScores_Interaction_DeletionSuppressors_K_lm.csv"), row.names = FALSE)
 
-      # Interaction plots for reference strain
-      variables <- c("L", "K", "r", "AUC")
-      reference_plot_configs <- interaction_plot_configs(df_reference, variables)
-      generate_and_save_plots(zscores_calculation_reference, out_dir, "RF_InteractionPlots", reference_plot_configs)
-
-      deletion_plot_configs <- interaction_plot_configs(df_deletion, variables)
-      generate_and_save_plots(zscores_calculations, out_dir, "InteractionPlots", deletion_plot_configs)
-
       # Correlation plots
       lm_list <- list(
         lm(Z_lm_K ~ Z_lm_L, data = zscores_interactions_filtered),
@@ -786,7 +920,7 @@ main <- function() {
 
       lm_summaries <- lapply(lm_list, summary)
       correlation_plot_config <- correlation_plot_configs(zscores_interactions_filtered, lm_list, lm_summaries)
-      generate_and_save_plots(zscores_interactions_filtered, output_dir, "CorrelationPlots", correlation_plot_config)
+      generate_and_save_plots(zscores_interactions_filtered, output_dir, correlation_plot_config)
       
       # Generate ranked plots
       rank_plot_config <- list(
@@ -796,7 +930,7 @@ main <- function() {
         list(x_var = "AUC_Rank", y_var = "Avg_Zscore_AUC", plot_type = "scatter", title = "Rank vs Avg Z score for AUC")
       )
       # Generate and save rank plots using the existing plotting framework
-      generate_and_save_plots(zscores_interactions_filtered, output_dir, "RankPlots", rank_plot_config)
+      generate_and_save_plots(zscores_interactions_filtered, output_dir, rank_plot_config)
     })
   })
 }