diff --git a/workflow/apps/r/calculate_interaction_zscores5.R b/workflow/apps/r/calculate_interaction_zscores5.R
index f603b89e..e0cf5831 100644
--- a/workflow/apps/r/calculate_interaction_zscores5.R
+++ b/workflow/apps/r/calculate_interaction_zscores5.R
@@ -245,27 +245,6 @@ calculate_summary_stats <- function(df, variables, group_vars = c("conc_num", "c
   return(summary_stats)
 }
 
-# Calculate L values within and outside 2SD of K
-calculate_l_2sd_of_k <- function(df, df_stats_by_k) {
-  # Join the statistics to the main dataframe
-  df_joined <- df %>%
-    filter(!is.na(L)) %>%
-    left_join(df_stats_by_k, by = "conc_num_factor")
-  
-  # Filter data within 2SD and outside 2SD
-  df_within_2sd_k <- df_joined %>%
-    filter(K >= (mean_K - 2 * sd_K) & K <= (mean_K + 2 * sd_K))
-  
-  df_outside_2sd_k <- df_joined %>%
-    filter(K < (mean_K - 2 * sd_K) | K > (mean_K + 2 * sd_K))
-  
-  # Select relevant columns to avoid duplicated columns from the join
-  df_within_2sd_k <- df_within_2sd_k %>% select(names(df))
-  df_outside_2sd_k <- df_outside_2sd_k %>% select(names(df))
-  
-  list(within_2sd_k = df_within_2sd_k, outside_2sd_k = df_outside_2sd_k)
-}
-
 # Ensure all plots are saved and printed to PDF
 save_plots <- function(file_name, plot_list, output_dir) {
   # Save to PDF
@@ -294,7 +273,6 @@ save_plots <- function(file_name, plot_list, output_dir) {
   })
 }
 
-
 # Calculate background strain mean values
 calculate_bg_means <- function(df_stats_by_l, df_stats_by_k, df_stats_by_r, df_stats_by_auc) {
   list(
@@ -573,11 +551,14 @@ main <- function() {
 
     # Flag and remove non-finite data, printing affected rows
     df_na_filtered <- df_na %>%
-    filter(if_any(c(L, r, AUC, K), ~ !is.finite(.))) %>%
-    {
-      if (nrow(.) > 0) message("Removing non-finite rows:\n", print(.))
-      df_na %>% filter(if_all(c(L, r, AUC, K), is.finite))
-    }
+      filter(if_any(c(L), ~ !is.finite(.))) %>% # Add L, r, AUC, K as needed for debugging
+      {
+        if (nrow(.) > 0) {
+          message("Removing non-finite rows:\n")
+          #print(.)
+        }
+        df_na %>% filter(if_all(c(L), is.finite)) # Add L, r, AUC, K as needed for debugging
+      }
     
     # # Generate QC PDFs and HTMLs
     # message("Generating QC plots")
@@ -596,10 +577,33 @@ main <- function() {
     write.csv(stats, file = file.path(out_dir, "SummaryStats_ALLSTRAINS.csv"), row.names = FALSE)
     stats_joined <- left_join(df_na, stats, by = c("conc_num", "conc_num_factor"))
 
+    # Create separate dataframes for each variable (we'll use later for plotting)
     stats_by_l <- stats_joined %>% select(starts_with("L_"), "OrfRep", "conc_num", "conc_num_factor")
     stats_by_k <- stats_joined %>% select(starts_with("K_"), "OrfRep", "conc_num", "conc_num_factor")
     stats_by_r <- stats_joined %>% select(starts_with("r_"), "OrfRep", "conc_num", "conc_num_factor")
     stats_by_auc <- stats_joined %>% select(starts_with("AUC_"), "OrfRep", "conc_num", "conc_num_factor")
+
+    stats_by_k_joined <- left_join(df_na, stats_by_k, by = c("conc_num_factor")) # TODO may need to add OrfRep, conc_num, etc
+    
+    # Filter data within 2SD
+    within_2sd_k <- stats_by_k_joined %>%
+      filter(K >= (mean_K - 2 * sd_K) & K <= (mean_K + 2 * sd_K))
+    
+    # Filter data outside 2SD
+    outside_2sd_k <- stats_by_k_joined %>%
+      filter(K < (mean_K - 2 * sd_K) | K > (mean_K + 2 * sd_K))
+
+    # Calculate summary statistics for L within and outside 2SD of K
+    message("Calculating summary statistics for L within 2SD of K")
+    l_within_2sd_k <- calculate_summary_stats(within_2sd_k, "L", group_vars = c("conc_num", "conc_num_factor"))
+    write.csv(l_within_2sd_k,
+      file = file.path(out_dir, "Max_Observed_L_Vals_for_spots_within_2sd_k.csv"),
+      row.names = FALSE)
+    message("Calculating summary statistics for for L outside 2SD of K")
+    l_outside_2sd_k <- calculate_summary_stats(outside_2sd_k, "L", group_vars = c("conc_num", "conc_num_factor"))
+    write.csv(l_outside_2sd_k,
+      file = file.path(out_dir, "Max_Observed_L_Vals_for_spots_outside_2sd_k.csv"),
+      row.names = FALSE)
     
     # Process background strains
     background_strains <- c("YDL227C")
@@ -630,26 +634,6 @@ main <- function() {
         file = file.path(out_dir, paste0("SummaryStats_BackgroundStrains_", strain, ".csv")),
         row.names = FALSE)
       stats_bg_joined <- left_join(df_bg, stats_bg, by = c("OrfRep", "Gene", "conc_num", "conc_num_factor"))
-
-      # Filter L values within and outside 2SD of K
-      results_2sd <- calculate_l_2sd_of_k(df_bg, stats_by_k_bg)
-      within_2sd_k <- results_2sd$within_2sd_k
-      outside_2sd_k <- results_2sd$outside_2sd_k
-      
-      # Calculate summary statistics for L within and outside 2SD of K
-      message("Calculating summary statistics for for L within 2SD of K")
-      l_within_2sd_k <- calculate_summary_stats(within_2sd_k, "L", group_vars = c("conc_num", "conc_num_factor"))
-      write.csv(l_within_2sd_k,
-        file = file.path(out_dir, "Max_Observed_L_Vals_for_spots_within_2sd_k.csv"),
-        row.names = FALSE)
-      message("Calculating summary statistics for for L outside 2SD of K")
-      l_outside_2sd_k <- calculate_summary_stats(outside_2sd_k, "L", group_vars = c("conc_num", "conc_num_factor"))
-      write.csv(l_outside_2sd_k,
-        file = file.path(out_dir, "Max_Observed_L_Vals_for_spots_outside_2sd_k.csv"),
-        row.names = FALSE)
-      
-      message("Generating Raw_L_vs_K_for_strains_outside_2sd_k plots")
-      generate_and_save_plots(outside_2sd_k, out_dir, "Raw_L_vs_K_for_strains_outside_2sd_k")
       
       message("Calculating background means")
       background_means <- calculate_bg_means(stats_by_l_bg, stats_by_k_bg, stats_by_r_bg, stats_by_auc_bg)