diff --git a/qhtcp-workflow/apps/r/calculate_interaction_zscores.R b/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
index 2b09829a..abd19b81 100644
--- a/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
+++ b/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
@@ -355,7 +355,7 @@ calculate_interaction_scores <- function(df, max_conc, variables, group_vars) {
     calculations_joined = calculations_joined))
 }
 
-generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_layout = NULL) {
+generate_and_save_plots <- function(out_dir, file_name, plot_configs, grid_layout = NULL) {
   message("Generating ", file_name, ".pdf and ", file_name, ".html")
 
   # Prepare lists to collect plots
@@ -410,19 +410,9 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
     }
 
     # Add interactive tooltips for plotly plots
-    tooltip_vars <- c("x", "y")
-    if (!is.null(config$tooltip_vars)) {
-      tooltip_vars <- config$tooltip_vars
-    } else {
-      # Include default variables based on config
-      if (!is.null(config$delta_bg_point) && config$delta_bg_point) {
-        tooltip_vars <- c(tooltip_vars, "OrfRep", "Gene", "delta_bg")
-      } else if (!is.null(config$gene_point) && config$gene_point) {
-        tooltip_vars <- c(tooltip_vars, "OrfRep", "Gene")
-      } else {
-        # Include x and y variables by default
-        tooltip_vars <- c("x", "y")
-      }
+    tooltip_vars <- c()
+    if (config$plot_type == "scatter") {
+      tooltip_vars <- c(config$x_var, config$y_var)
     }
 
     # Convert to plotly object
@@ -437,7 +427,7 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
   }
 
   # Save static PDF plots
-  pdf(file.path(output_dir, paste0(file_name, ".pdf")), width = 14, height = 9)
+  pdf(file.path(out_dir, paste0(file_name, ".pdf")), width = 14, height = 9)
   lapply(static_plots, print)
   dev.off()
 
@@ -445,16 +435,11 @@ generate_and_save_plots <- function(output_dir, file_name, plot_configs, grid_la
   combined_plot <- subplot(plotly_plots,
     nrows = ifelse(is.null(grid_layout$nrow), length(plotly_plots), grid_layout$nrow),
     margin = 0.05)
-  saveWidget(combined_plot, file = file.path(output_dir, paste0(file_name, ".html")), selfcontained = TRUE)
+  saveWidget(combined_plot, file = file.path(out_dir, paste0(file_name, ".html")), selfcontained = TRUE)
 }
 
 generate_scatter_plot <- function(plot, config) {
   
-  # Build the aes mapping with color if specified
-  if (!is.null(config$color_var)) {
-    plot <- plot + aes(color = .data[[config$color_var]])
-  }
-  
   # Determine Shape, Size, and Position for geom_point
   shape <- if (!is.null(config$shape)) config$shape else 3
   size <- if (!is.null(config$size)) config$size else 0.1
@@ -462,7 +447,6 @@ generate_scatter_plot <- function(plot, config) {
   
   # Add geom_point with determined parameters
   plot <- plot + geom_point(
-    aes(color = .data[[config$color_var]]),
     shape = shape,
     size = size,
     position = position
@@ -470,7 +454,6 @@ generate_scatter_plot <- function(plot, config) {
 
   if (!is.null(config$cyan_points)) {
     plot <- plot + geom_point(
-      data = subset(config$df, is_cyan_point == TRUE),
       aes(x = .data[[config$x_var]], y = .data[[config$y_var]]),
       color = "cyan",
       shape = 3,
@@ -618,6 +601,38 @@ generate_box_plot <- function(plot, config) {
   return(plot)
 }
 
+generate_plate_analysis_plot_configs <- function(variables, stages = c("before", "after"),
+  df_before = NULL, df_after = NULL, plot_type = "scatter") {
+  plots <- list()
+  for (var in variables) {
+    for (stage in stages) {
+      df_plot <- if (stage == "before") df_before else df_after
+      
+      # Adjust settings based on plot_type
+      if (plot_type == "scatter") {
+        error_bar <- TRUE
+        position <- "jitter"
+      } else if (plot_type == "box") {
+        error_bar <- FALSE
+        position <- NULL
+      }
+      
+      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_factor",
+        position = position
+      )
+      plots <- append(plots, list(config))
+    }
+  }
+  return(plots)
+}
+
 generate_interaction_plot_configs <- function(df, variables) {
 
   configs <- list()
@@ -842,7 +857,7 @@ generate_rank_plot_configs <- function(df_filtered, variables, is_lm = FALSE) {
         color_var = "Overlap",
         x_label = x_var,
         y_label = y_var,
-        rectangles = rectangles  # Add rectangles configuration
+        rectangles = rectangles
       )
     }
   }
@@ -871,7 +886,7 @@ generate_correlation_plot_configs <- function(df) {
     config <- list(
       df = df,
       x_var = rel$x,
-      y_var = rel.y,
+      y_var = rel$y,
       plot_type = "scatter",
       title = rel$label,
       x_label = paste("z-score", gsub("Z_lm_", "", rel$x)),
@@ -1137,79 +1152,31 @@ main <- function() {
       )
     )
 
-    plate_analysis_plots <- list()
-    for (var in summary_vars) {
-      for (stage in c("before", "after")) {
-        if (stage == "before") {
-          df_plot <- df_filtered_stats
-        } else {
-          df_plot <- df_na_filtered_stats
-        }
-        
-        config <- list(
-          df = df_plot,
-          x_var = "scan",
-          y_var = var,
-          plot_type = "scatter",
-          title = paste("Plate analysis by Drug Conc for", var, stage, "quality control"),
-          error_bar = TRUE,
-          color_var = "conc_num_factor",
-          position = "jitter")
+    plate_analysis_plot_configs <- generate_plate_analysis_plot_configs(
+      variables = summary_vars,
+      df_before = df_filtered_stats,
+      df_after = df_na_filtered_stats,
+    )
 
-        plate_analysis_plots <- append(plate_analysis_plots, list(config))
-      }
-    }
+    plate_analysis_box_plot_configs <- generate_plate_analysis_plot_configs(
+      variables = summary_vars,
+      df_before = df_filtered_stats,
+      df_after = df_na_filtered_stats,
+      plot_type = "box"
+    )
 
-    plate_analysis_boxplots <- list()
-    for (var in summary_vars) {
-      for (stage in c("before", "after")) {
-        if (stage == "before") {
-          df_plot <- df_filtered_stats
-        } else {
-          df_plot <- df_na_filtered_stats
-        }
-        
-        config <- list(
-          df = df_plot,
-          x_var = "scan",
-          y_var = var,
-          plot_type = "box",
-          title = paste("Plate analysis by Drug Conc for", var, stage, "quality control"),
-          error_bar = FALSE,
-          color_var = "conc_num_factor")
+    plate_analysis_no_zeros_plot_configs <- generate_plate_analysis_plot_configs(
+      variables = summary_vars,
+      stages = c("after"),  # Only after QC
+      df_after = df_no_zeros_filtered_stats,
+    )
 
-        plate_analysis_boxplots <- append(plate_analysis_boxplots, list(config))
-      }
-    }
-
-    plate_analysis_no_zeros_plots <- list()
-    for (var in summary_vars) {
-      config <- list(
-        df = df_no_zeros_filtered_stats,
-        x_var = "scan",
-        y_var = var,
-        plot_type = "scatter",
-        title = paste("Plate analysis by Drug Conc for", var, "after quality control"),
-        error_bar = TRUE,
-        color_var = "conc_num_factor",
-        position = "jitter")
-
-      plate_analysis_no_zeros_plots <- append(plate_analysis_no_zeros_plots, list(config))
-    }
-
-    plate_analysis_no_zeros_boxplots <- list()
-    for (var in summary_vars) {
-      config <- list(
-        df = df_no_zeros_filtered_stats,
-        x_var = "scan",
-        y_var = var,
-        plot_type = "box",
-        title = paste("Plate analysis by Drug Conc for", var, "after quality control"),
-        error_bar = FALSE,
-        color_var = "conc_num_factor"
-      )
-      plate_analysis_no_zeros_boxplots <- append(plate_analysis_no_zeros_boxplots, list(config))
-    }
+    plate_analysis_no_zeros_boxplot_configs <- generate_plate_analysis_plot_configs(
+      variables = summary_vars,
+      stages = c("after"),  # Only after QC
+      df_after = df_no_zeros_filtered_stats,
+      plot_type = "box"
+    )
 
     l_outside_2sd_k_plots <- list(
       list(
@@ -1239,16 +1206,16 @@ main <- function() {
       )
     )
 
-    # message("Generating quality control plots")
-    # generate_and_save_plots(out_dir_qc, "L_vs_K_before_quality_control", l_vs_k_plots)
-    # generate_and_save_plots(out_dir_qc, "frequency_delta_background", frequency_delta_bg_plots)
-    # generate_and_save_plots(out_dir_qc, "L_vs_K_above_threshold", above_threshold_plots)
-    # generate_and_save_plots(out_dir_qc, "plate_analysis", plate_analysis_plots)
-    # generate_and_save_plots(out_dir_qc, "plate_analysis_boxplots", plate_analysis_boxplots)
-    # generate_and_save_plots(out_dir_qc, "plate_analysis_no_zeros", plate_analysis_no_zeros_plots)
-    # generate_and_save_plots(out_dir_qc, "plate_analysis_no_zeros_boxplots", plate_analysis_no_zeros_boxplots)
-    # generate_and_save_plots(out_dir_qc, "L_vs_K_for_strains_2SD_outside_mean_K", l_outside_2sd_k_plots)
-    # generate_and_save_plots(out_dir_qc, "delta_background_vs_K_for_strains_2sd_outside_mean_K", delta_bg_outside_2sd_k_plots)
+    message("Generating quality control plots")
+    generate_and_save_plots(out_dir_qc, "L_vs_K_before_quality_control", l_vs_k_plots)
+    generate_and_save_plots(out_dir_qc, "frequency_delta_background", frequency_delta_bg_plots)
+    generate_and_save_plots(out_dir_qc, "L_vs_K_above_threshold", above_threshold_plots)
+    generate_and_save_plots(out_dir_qc, "plate_analysis", plate_analysis_plot_configs)
+    generate_and_save_plots(out_dir_qc, "plate_analysis_boxplots", plate_analysis_boxplot_configs)
+    generate_and_save_plots(out_dir_qc, "plate_analysis_no_zeros", plate_analysis_no_zeros_plot_configs)
+    generate_and_save_plots(out_dir_qc, "plate_analysis_no_zeros_boxplots", plate_analysis_no_zeros_boxplot_configs)
+    generate_and_save_plots(out_dir_qc, "L_vs_K_for_strains_2SD_outside_mean_K", l_outside_2sd_k_plots)
+    generate_and_save_plots(out_dir_qc, "delta_background_vs_K_for_strains_2sd_outside_mean_K", delta_bg_outside_2sd_k_plots)
 
     # Process background strains
     bg_strains <- c("YDL227C")
@@ -1399,7 +1366,7 @@ main <- function() {
         variables = interaction_vars,
         is_lm = FALSE
       )
-      generate_and_save_plots(output_dir = out_dir, file_name = "RankPlots",
+      generate_and_save_plots(out_dir = out_dir, file_name = "RankPlots",
         plot_configs = rank_plot_configs, grid_layout = list(ncol = 3, nrow = 2))
 
       message("Generating ranked linear model plots")
@@ -1408,7 +1375,7 @@ main <- function() {
         variables = interaction_vars,
         is_lm = TRUE
       )
-      generate_and_save_plots(output_dir = out_dir, file_name = "RankPlots_lm",
+      generate_and_save_plots(out_dir = out_dir, file_name = "RankPlots_lm",
         plot_configs = rank_lm_plot_configs, grid_layout = list(ncol = 3, nrow = 2))
 
       message("Filtering and reranking plots")
@@ -1449,7 +1416,7 @@ main <- function() {
 
       message("Generating filtered ranked plots")
       generate_and_save_plots(
-        output_dir = out_dir,
+        out_dir = out_dir,
         file_name = "RankPlots_na_rm",
         plot_configs = rank_plot_filtered_configs,
         grid_layout = list(ncol = 3, nrow = 2))
@@ -1461,7 +1428,7 @@ main <- function() {
         is_lm = TRUE
       )
       generate_and_save_plots(
-        output_dir = out_dir,
+        out_dir = out_dir,
         file_name = "RankPlots_lm_na_rm",
         plot_configs = rank_plot_lm_filtered_configs,
         grid_layout = list(ncol = 3, nrow = 2))
@@ -1469,7 +1436,7 @@ main <- function() {
       message("Generating correlation plots")
       correlation_plot_configs <- generate_correlation_plot_configs(zscores_interactions_filtered)
       generate_and_save_plots(
-        output_dir = out_dir,
+        out_dir = out_dir,
         file_name = "Avg_Zscore_vs_lm_NA_rm",
         plot_configs = correlation_plot_configs,
         grid_layout = list(ncol = 2, nrow = 2))