diff --git a/qhtcp-workflow/apps/r/calculate_interaction_zscores.R b/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
index 1161c7c0..6ce22a06 100644
--- a/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
+++ b/qhtcp-workflow/apps/r/calculate_interaction_zscores.R
@@ -656,7 +656,11 @@ generate_interaction_plot_configs <- function(df, variables) {
     AUC = c(-6500, 6500)
   )
 
-  df_filtered <- filter_data(df, variables, filter_na = TRUE, limits_map = limits_map)
+  # Filtering out NAs and outlying values
+  df_filtered <- df %>%
+    filter(across(names(limits_map),
+      ~ !is.na(.x) &
+      between(.x, limits_map[[.names]][1], limits_map[[.names]][2])))
 
   # Define annotation label functions
   generate_annotation_labels <- function(df, var, annotation_name) {
@@ -747,7 +751,7 @@ generate_interaction_plot_configs <- function(df, variables) {
   return(configs)
 }
 
-generate_rank_plot_configs <- function(df, variables, is_lm = FALSE, overlap_color = FALSE) {
+generate_rank_plot_configs <- function(df, variables, is_lm = FALSE, adjust = FALSE, overlap_color = FALSE) {
   
   sd_bands <- c(1, 2, 3)
 
@@ -977,39 +981,6 @@ generate_correlation_plot_configs <- function(df) {
   return(configs)
 }
 
-filter_data <- function(df, variables, filter_nf = FALSE, filter_na = FALSE, limits_map = NULL) {
-
-  avg_zscore_cols <- paste0("Avg_Zscore_", variables)
-  z_lm_cols <- paste0("Z_lm_", variables)
-  rank_avg_zscore_cols <- paste0("Rank_", variables)
-  rank_z_lm_cols <- paste0("Rank_lm_", variables)
-
-  if (filter_nf) {
-    message("Filtering non-finite values")
-    df <- df %>%
-      filter(if_all(all_of(variables), ~ is.finite(.)))
-  }
-
-  if (filter_na) {
-    message("Filtering NA values")
-    df <- df %>%
-      filter(if_all(all_of(variables), ~ !is.na(.)))
-  }
-
-  if (!is.null(limits_map)) {
-    message("Filtering data outside y-limits (for plotting)")
-    for (variable in names(limits_map)) {
-      if (variable %in% variables) {
-        ylim_vals <- limits_map[[variable]]
-        df <- df %>%
-          filter(.data[[variable]] >= ylim_vals[1] & .data[[variable]] <= ylim_vals[2])
-      }
-    }
-  }
-
-  return(df)
-}
-
 main <- function() {
   lapply(names(args$experiments), function(exp_name) {
     exp <- args$experiments[[exp_name]]