diff --git a/R/colocboost.R b/R/colocboost.R
index 91890f1..19904ae 100644
--- a/R/colocboost.R
+++ b/R/colocboost.R
@@ -157,7 +157,6 @@ colocboost <- function(X = NULL, Y = NULL, # individual data
                        multicorrection_cut = 1,
                        ash_prior = "normal", # only applicable if func_multicorrection = lfsr
                        p.adjust.methods = "fdr",
-                       npc_cutoff = 0.7,
                        check_null = 0.1, # the cut off value for change conditional objective function
                        check_null_method = "profile",
                        check_null_max = 0.02,
@@ -568,7 +567,6 @@ colocboost <- function(X = NULL, Y = NULL, # individual data
                                      coverage = coverage,
                                      func_intw = func_intw,
                                      alpha = alpha,
-                                     npc_cutoff = npc_cutoff,
                                      check_null = check_null,
                                      check_null_method = check_null_method,
                                      check_null_max = check_null_max,
diff --git a/R/colocboost_assemble.R b/R/colocboost_assemble.R
index 9de7f39..4677859 100644
--- a/R/colocboost_assemble.R
+++ b/R/colocboost_assemble.R
@@ -26,7 +26,6 @@ colocboost_assemble <- function(cb_obj,
                                 check_null = 0.1,
                                 check_null_method = "profile",
                                 check_null_max=2e-5,
-                                npc_cutoff = 0.7,
                                 dedup = TRUE,
                                 overlap = TRUE,
                                 n_purity = 100,
@@ -193,7 +192,7 @@ colocboost_assemble <- function(cb_obj,
         # - colocalization results
         cb_obj$cb_model_para$alpha <- alpha
         cb_obj$cb_model_para$coverage <- coverage
-        cos_results <- get_cos_details(cb_obj, coloc_out = past_out$cos$cos, data_info = data_info, npc_cutoff = npc_cutoff)
+        cos_results <- get_cos_details(cb_obj, coloc_out = past_out$cos$cos, data_info = data_info)
         cb_output <- list("vcp" = cos_results$vcp,
                           "cos_details" = cos_results$cos_results,
                           "data_info" = data_info,
diff --git a/R/colocboost_output.R b/R/colocboost_output.R
index 7f2899f..8a84e9b 100644
--- a/R/colocboost_output.R
+++ b/R/colocboost_output.R
@@ -75,7 +75,7 @@ get_data_info <- function(cb_obj){
 
 #' @noRd
 #' @keywords cb_post_inference
-get_cos_details <- function(cb_obj, coloc_out, data_info = NULL, npc_cutoff = 0.7){
+get_cos_details <- function(cb_obj, coloc_out, data_info = NULL){
 
     if (is.null(data_info))
         data_info <- get_data_info(cb_obj)
@@ -86,7 +86,7 @@ get_cos_details <- function(cb_obj, coloc_out, data_info = NULL, npc_cutoff = 0.
     if (length(coloc_sets)!=0){
 
       # - colocalization outcome configurations
-      tmp <- get_cos_evidence(cb_obj, coloc_out, data_info, npc_cutoff = npc_cutoff)
+      tmp <- get_cos_evidence(cb_obj, coloc_out, data_info)
       normalization_evidence <- tmp$normalization_evidence
       npc <- tmp$npc
       
diff --git a/R/colocboost_utils.R b/R/colocboost_utils.R
index 000bea0..4b5731b 100644
--- a/R/colocboost_utils.R
+++ b/R/colocboost_utils.R
@@ -339,7 +339,7 @@ get_between_purity = function (pos1, pos2, X=NULL, Xcorr=NULL, N = NULL, miss_id
 }
 
 
-get_cos_evidence <- function(cb_obj, coloc_out, data_info, npc_cutoff = 0.7){
+get_cos_evidence <- function(cb_obj, coloc_out, data_info){
 
   get_cos_config <- function(w, config_idx, alpha = 1.5, coverage = 0.95){
     
@@ -395,7 +395,7 @@ get_cos_evidence <- function(cb_obj, coloc_out, data_info, npc_cutoff = 0.7){
   }
   
   # - calculate best configuration likelihood explained by minimal configuration
-  get_normalization_evidence <- function(profile_change, null_max, outcomes, outcome_names, npc_cutoff = 0.7) {
+  get_normalization_evidence <- function(profile_change, null_max, outcomes, outcome_names) {
     # Define the exponential likelihood ratio normalization (ELRN)
     logLR_normalization <- function(ratio) { 1 - exp( - 2*ratio ) }
     
@@ -405,10 +405,16 @@ get_cos_evidence <- function(cb_obj, coloc_out, data_info, npc_cutoff = 0.7){
     rownames(df) <- outcome_names[outcomes]
     sorted_df <- df[order(-df$relative_logLR), ]
     sorted_df$strong_effect <- sorted_df$relative_logLR >= 1
-    sorted_df$suggestive_effect <- sorted_df$npc_outcome >= npc_cutoff
     return(sorted_df)
   }
   
+  get_npuc <- function(npc_outcome){
+    # npuc_outcome <- sapply(1:length(npc_outcome), function(i) npc_outcome[i]*prod(1-npc_outcome[-i]) )
+    # 1 - prod(1-npuc_outcome)
+    max_idx <- which.max(npc_outcome)
+    npc_outcome[max_idx] * prod(1 - npc_outcome[-max_idx])
+  }
+  
   avWeight <- coloc_out$avWeight
   cs_change <- coloc_out$cs_change
   check_null_max <- sapply(cb_obj$cb_model, function(cb) cb$check_null_max)
@@ -426,12 +432,10 @@ get_cos_evidence <- function(cb_obj, coloc_out, data_info, npc_cutoff = 0.7){
     })
     normalization_evidence[[i]] <- get_normalization_evidence(profile_change = profile_change_outcome, 
                                                    null_max = check_null_max[outcomes], 
-                                                   outcomes, outcome_names, npc_cutoff = npc_cutoff)
+                                                   outcomes, outcome_names)
     
     # - calcualte CoS colocalization probability (CCP) and CoS uncolocalization probability (UCCP) 
-    npc_outcome <- normalization_evidence[[i]]$npc_outcome 
-    max_idx <- which.max(npc_outcome)
-    npuc <- npc_outcome[max_idx] * prod(1 - npc_outcome[-max_idx])
+    npuc <- get_npuc(normalization_evidence[[i]]$npc_outcome)
     npc[i] <- 1 - npuc
   }
   names(normalization_evidence) <- names(npc) <- names(coloc_out$cos)