diff --git a/qhtcp-workflow/apps/r/calculate_interaction_zscores.R b/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
index 1753cead..3374eb50 100644
--- a/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
+++ b/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
@@ -787,46 +787,40 @@ filter_and_print_non_finite <- function(df, vars_to_check, print_vars) {
   df %>% filter(if_all(all_of(vars_to_check), is.finite))
 }
 
-filter_data_for_plots <- function(df, variables, missing = TRUE, limits_map = NULL) {
-
-  # Print missing data and out-of-range data separately
+filter_data_for_plots <- function(df, variables, missing = FALSE, limits_map = NULL) {
+  
+  # Loop through each variable to filter and print missing/out-of-range data
   for (variable in variables) {
     y_var_sym <- sym(variable)
-
+    
+    # Filter missing data
     if (missing) {
       missing_data <- df %>% filter(is.na(!!y_var_sym))
       if (nrow(missing_data) > 0) {
         message("Missing data for variable ", variable, ":")
         print(missing_data)
       }
+      df <- df %>% filter(!is.na(!!y_var_sym))
     }
-
+    
+    # Filter out-of-range data if limits_map is provided
     if (!is.null(limits_map)) {
-      # Get y-limits for the variable
       ylim_vals <- limits_map[[variable]]
-
-      # Identify out-of-range data and print it
+      
+      # Print and filter out-of-range data
       out_of_range_data <- df %>% filter(
-        !is.na(!!y_var_sym) &
-          (!!y_var_sym < min(ylim_vals, na.rm = TRUE) | !!y_var_sym > max(ylim_vals, na.rm = TRUE))
+        !!y_var_sym < ylim_vals[1] | !!y_var_sym > ylim_vals[2]
       )
       if (nrow(out_of_range_data) > 0) {
         message("Out-of-range data for variable ", variable, ":")
         print(out_of_range_data)
+      df <- df %>%
+        filter(!!y_var_sym >= ylim_vals[1] & !!y_var_sym <= ylim_vals[2])
       }
     }
   }
-
-  # Filter data by checking if all variables are within the specified limits
-  if (!is.null(limits_map)) {
-    df_filtered <- df %>%
-      filter(if_all(all_of(variables), ~ !is.na(.))) %>%  # Check for non-NA values
-      filter(if_all(all_of(variables), ~ . >= limits_map[[cur_column()]][1] & . <= limits_map[[cur_column()]][2]))
-  } else {
-    df_filtered <- df %>% filter(if_all(all_of(variables), ~ !is.na(.)))
-  }
-
-  return(df_filtered)
+  
+  return(df)
 }
 
 main <- function() {