diff --git a/R/colocboost_output.R b/R/colocboost_output.R
index 7214863..fb9bd92 100644
--- a/R/colocboost_output.R
+++ b/R/colocboost_output.R
@@ -42,10 +42,11 @@
 #'   \itemize{
 #'     \item \code{cos_summary}: As described above
 #'     \item \code{ucos_summary}: A summary table for trait-specific (uncolocalized) effects
-#'     \item \code{ambiguous_ucos_summary}: A summary table for ambiguous colocalization events from trait-specific effects
+#'     \item \code{ambiguous_cos_summary}: A summary table for ambiguous colocalization events from trait-specific effects
 #'   }
 #' }
-#' @details When \code{summary_level = 2} or \code{summary_level = 3}, additional details for trait-specific effects and ambiguous 
+#' @details When \code{summary_level = 1}, additional details and examples are introduced in \code{\link{get_cos_summary}}. 
+#' When \code{summary_level = 2} or \code{summary_level = 3}, additional details for trait-specific effects and ambiguous 
 #' colocalization events are included. See \code{\link{get_ucos_summary}} for details on these tables.
 #' 
 #' @examples
@@ -101,13 +102,13 @@ get_colocboost_summary <- function(cb_output,
     if (summary_level == 3){
       ucos_summary <- get_ucos_summary(
         cb_output, outcome_names, region_name,
-         ambiguous_ucos = TRUE,
+         ambiguous_cos = TRUE,
          min_abs_corr_between_ucos = min_abs_corr_between_ucos,
          median_abs_corr_between_ucos = median_abs_corr_between_ucos
       )
       return(list("cos_summary" = cos_summary, 
                   "ucos_summary" = ucos_summary$ucos_summary,
-                  "ambiguous_ucos_summary" = ucos_summary$ambiguous_ucos_summary))
+                  "ambiguous_cos_summary" = ucos_summary$ambiguous_cos_summary))
     }
                   
 }
@@ -408,13 +409,13 @@ get_robust_colocalization <- function(cb_output,
 #' @param tol A small, non-negative number specifying the convergence tolerance for checking the overlap of the variables in different sets.
 #'
 #' @return A \code{"colocboost"} object of colocboost output with additional elements:
-#' \item{ambiguous_ucos}{If exists, a list of ambiguous trait-specific (uncolocalized) effects.}
+#' \item{ambiguous_cos}{If exists, a list of ambiguous trait-specific (uncolocalized) effects.}
 #'
 #' @examples
 #' data(Ambiguous_Colocalization)
 #' test_colocboost_results <- Ambiguous_Colocalization$ColocBoost_Results
 #' res <- get_ambiguous_colocalization(test_colocboost_results)
-#' names(res$ambigous_ucos)
+#' names(res$ambiguous_cos)
 #' 
 #' @source See detailed instructions in our tutorial portal: 
 #' \url{https://statfungen.github.io/colocboost/articles/Interpret_ColocBoost_Output.html}
@@ -503,50 +504,50 @@ get_ambiguous_colocalization <- function(cb_output,
     potential_merged <- lapply(temp, function(x) as.numeric(unlist(strsplit(x, ";"))))
     potential_merged <- potential_merged[which(sapply(potential_merged, length) >= 2)]
 
-    ambigous_events <- list()
-    ambigouse_ucos_names <- c()
+   ambiguous_events <- list()
+    ambiguous_ucos_names <- c()
     for (i in 1:length(potential_merged)) {
       idx <- potential_merged[[i]]
       test_outcome <- unique(unlist(ucos_details$ucos_outcomes$outcome_index[idx]))
       if (length(test_outcome) == 1) next
-      ambigouse_ucos_names[i] <- paste0(names(ucos_details$ucos$ucos_index)[idx], collapse = ";")
+      ambiguous_ucos_names[i] <- paste0(names(ucos_details$ucos$ucos_index)[idx], collapse = ";")
       tmp <- list(
-        ambigouse_ucos = list(
+        ambiguous_cos = list(
           ucos_index = ucos_details$ucos$ucos_index[idx],
           ucos_variables = ucos_details$ucos$ucos_variables[idx]
         ),
-        ambigouse_ucos_overlap = list(
+        ambiguous_cos_overlap = list(
           ucos_index = Reduce(intersect, ucos_details$ucos$ucos_index[idx]),
           ucos_variables = Reduce(intersect, ucos_details$ucos$ucos_variables[idx])
         ),
-        ambigouse_ucos_union = list(
+        ambiguous_cos_union = list(
           ucos_index = Reduce(union, ucos_details$ucos$ucos_index[idx]),
           ucos_variables = Reduce(union, ucos_details$ucos$ucos_variables[idx])
         ),
-        ambigouse_ucos_outcomes = list(
+        ambiguous_cos_outcomes = list(
           outcome_idx = unique(unlist(ucos_details$ucos_outcomes$outcome_index[idx])),
           outcome_name = unique(unlist(ucos_details$ucos_outcomes$outcome_name[idx]))
         ),
-        ambigous_ucos_weight = ucos_details$ucos_weight[idx],
-        ambigous_ucos_puriry = list(
+        ambigous_cos_weight = ucos_details$ucos_weight[idx],     
+        ambigous_cos_purity = list(            
           min_abs_cor = min_abs_cor[idx, idx],
           median_abs_cor = median_abs_cor[idx, idx],
           max_abs_cor = max_abs_cor[idx, idx]
         )
       )
-      w <- tmp$ambigous_ucos_weight
+      w <- tmp$ambigous_cos_weight
       w <- do.call(cbind, w)
       tmp$recalibrated_cos_vcp <- get_integrated_weight(w)
       tmp$recalibrated_cos <- list(
         "cos_index" = unlist(get_in_cos(tmp$recalibrated_cos_vcp)),
         "cos_variables" = lapply(unlist(get_in_cos(tmp$recalibrated_cos_vcp)), function(idx) cb_output$data_info$variables[idx])
       )
-      ambigous_events[[i]] <- tmp
+      ambiguous_events[[i]] <- tmp
     }
-    names(ambigous_events) <- ambigouse_ucos_names
-    message(paste("There are", length(ambigous_events), "ambiguous trait-specific effects."))
+    names(ambiguous_events) <- ambiguous_ucos_names
+    message(paste("There are", length(ambiguous_events), "ambiguous trait-specific effects."))
 
-    cb_output$ambigous_ucos <- ambigous_events
+    cb_output$ambiguous_cos <- ambiguous_events
     return(cb_output)
           
 }
@@ -700,7 +701,7 @@ get_cos_summary <- function(cb_output,
 #' @param cb_output Output object from `colocboost` analysis
 #' @param outcome_names Optional vector of names of outcomes, which has the same order as Y in the original analysis.
 #' @param region_name Optional character string. When provided, adds a column with this gene name to the output table for easier filtering in downstream analyses.
-#' @param ambiguous_ucos Logical indicating whether to include ambiguous colocalization events. The default is FALSE.
+#' @param ambiguous_cos Logical indicating whether to include ambiguous colocalization events. The default is FALSE.
 #' @param min_abs_corr_between_ucos Minimum absolute correlation for variants across two trait-specific (uncolocalized) effects to be considered colocalized. The default is 0.5.
 #' @param median_abs_corr_between_ucos Median absolute correlation for variants across two trait-specific (uncolocalized) effects to be considered colocalized. The default is 0.8.
 #' 
@@ -720,7 +721,7 @@ get_cos_summary <- function(cb_output,
 #'     \item \code{ucos_variables_vpa}: Variant-level probability of association (VPA) for all variables in the confidence set
 #'     \item \code{region_name}: Region name if provided through the region_name parameter
 #'   }
-#'   \item \code{ambiguous_ucos_summary}: A summary table for ambiguous colocalization events with the following columns:
+#'   \item \code{ambiguous_cos_summary}: A summary table for ambiguous colocalization events with the following columns:
 #'   \itemize{
 #'     \item \code{outcomes}: Outcome in the ambiguous colocalization event
 #'     \item \code{ucos_id}: Unique identifiers for the ambiguous event 
@@ -761,7 +762,7 @@ get_cos_summary <- function(cb_output,
 #' @family colocboost_utilities
 #' @export
 get_ucos_summary <- function(cb_output, outcome_names = NULL, region_name = NULL, 
-                             ambiguous_ucos = FALSE,
+                             ambiguous_cos = FALSE,
                              min_abs_corr_between_ucos = 0.5, 
                              median_abs_corr_between_ucos = 0.8) {
 
@@ -815,22 +816,22 @@ get_ucos_summary <- function(cb_output, outcome_names = NULL, region_name = NULL
     summary_table$region_name <- region_name
   }
   summary_table <- as.data.frame(summary_table)
-  if (!ambiguous_ucos) return(summary_table)
+  if (!ambiguous_cos) return(summary_table)
 
 
   # advanced summary for ambiguous colocalization at post-processing
   output_summary <- list(
     ucos_summary = summary_table,
-    ambiguous_ucos_summary = NULL
+    ambiguous_cos_summary = NULL
   )
   test <- get_ambiguous_colocalization(
     cb_output,
     min_abs_corr_between_ucos = min_abs_corr_between_ucos,
     median_abs_corr_between_ucos = median_abs_corr_between_ucos
   )
-  if (length(test$ambigous_ucos) == 0) return(output_summary)
+  if (length(test$ambiguous_cos) == 0) return(output_summary)
 
-  ambiguous_results <- test$ambigous_ucos
+  ambiguous_results <- test$ambiguous_cos
   ambiguous_summary <- matrix(NA, nrow = length(ambiguous_results), ncol = 10)
   colnames(ambiguous_summary) <- c(
     "outcomes", "ucos_id", "min_between_purity", "median_between_purity",
@@ -838,12 +839,12 @@ get_ucos_summary <- function(cb_output, outcome_names = NULL, region_name = NULL
     "recalibrated_index", "recalibrated_variables", "recalibrated_variables_vcp"
   )
 
-  ambiguous_summary[, 1] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$ambigouse_ucos_outcomes$outcome_name, collapse = "; ")))
+  ambiguous_summary[, 1] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$ambiguous_cos_outcomes$outcome_name, collapse = "; ")))
   ambiguous_summary[, 2] <- names(ambiguous_results)
-  ambiguous_summary[, 3] <- sapply(ambiguous_results, function(tmp) max(tmp$ambigous_ucos_puriry$min_abs_cor[lower.tri(tmp$ambigous_ucos_puriry$min_abs_cor)]) )
-  ambiguous_summary[, 4] <- sapply(ambiguous_results, function(tmp) max(tmp$ambigous_ucos_puriry$median_abs_cor[lower.tri(tmp$ambigous_ucos_puriry$median_abs_cor)]) )
-  ambiguous_summary[, 5] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$ambigouse_ucos_overlap$ucos_index, collapse = "; ")))
-  ambiguous_summary[, 6] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$ambigouse_ucos_overlap$ucos_variables, collapse = "; ")))
+  ambiguous_summary[, 3] <- sapply(ambiguous_results, function(tmp) max(tmp$ambigous_cos_purity$min_abs_cor[lower.tri(tmp$ambigous_cos_purity$min_abs_cor)]) )
+  ambiguous_summary[, 4] <- sapply(ambiguous_results, function(tmp) max(tmp$ambigous_cos_purity$median_abs_cor[lower.tri(tmp$ambigous_cos_purity$median_abs_cor)]) )
+  ambiguous_summary[, 5] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$ambiguous_cos_overlap$ucos_index, collapse = "; ")))
+  ambiguous_summary[, 6] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$ambiguous_cos_overlap$ucos_variables, collapse = "; ")))
   ambiguous_summary[, 7] <- as.numeric(sapply(ambiguous_results, function(tmp) length(tmp$recalibrated_cos$cos_index)))
   ambiguous_summary[, 8] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$recalibrated_cos$cos_index, collapse = "; ")))
   ambiguous_summary[, 9] <- unlist(sapply(ambiguous_results, function(tmp) paste0(tmp$recalibrated_cos$cos_variables, collapse = "; ")))
@@ -851,7 +852,7 @@ get_ucos_summary <- function(cb_output, outcome_names = NULL, region_name = NULL
   if (!is.null(region_name)) {
     ambiguous_summary$region_name <- region_name
   }
-  output_summary$ambiguous_ucos_summary <- as.data.frame(ambiguous_summary)
+  output_summary$ambiguous_cos_summary <- as.data.frame(ambiguous_summary)
 
   return(output_summary)
 }
diff --git a/data/Ambiguous_Colocalization.rda b/data/Ambiguous_Colocalization.rda
index 0063776..b36f259 100644
Binary files a/data/Ambiguous_Colocalization.rda and b/data/Ambiguous_Colocalization.rda differ
diff --git a/man/get_ambiguous_colocalization.Rd b/man/get_ambiguous_colocalization.Rd
index 44d64a8..1aeb315 100644
--- a/man/get_ambiguous_colocalization.Rd
+++ b/man/get_ambiguous_colocalization.Rd
@@ -26,7 +26,7 @@ get_ambiguous_colocalization(
 }
 \value{
 A \code{"colocboost"} object of colocboost output with additional elements:
-\item{ambiguous_ucos}{If exists, a list of ambiguous trait-specific (uncolocalized) effects.}
+\item{ambiguous_cos}{If exists, a list of ambiguous trait-specific (uncolocalized) effects.}
 }
 \description{
 \code{get_ambiguous_colocalization} get the colocalization by discarding the weaker colocalization events or colocalized outcomes
@@ -35,7 +35,7 @@ A \code{"colocboost"} object of colocboost output with additional elements:
 data(Ambiguous_Colocalization)
 test_colocboost_results <- Ambiguous_Colocalization$ColocBoost_Results
 res <- get_ambiguous_colocalization(test_colocboost_results)
-names(res$ambigous_ucos)
+names(res$ambiguous_cos)
 
 }
 \seealso{
diff --git a/man/get_colocboost_summary.Rd b/man/get_colocboost_summary.Rd
index 255e832..7453d8e 100644
--- a/man/get_colocboost_summary.Rd
+++ b/man/get_colocboost_summary.Rd
@@ -63,7 +63,7 @@ A list containing results from the ColocBoost analysis:
 \itemize{
 \item \code{cos_summary}: As described above
 \item \code{ucos_summary}: A summary table for trait-specific (uncolocalized) effects
-\item \code{ambiguous_ucos_summary}: A summary table for ambiguous colocalization events from trait-specific effects
+\item \code{ambiguous_cos_summary}: A summary table for ambiguous colocalization events from trait-specific effects
 }
 }
 }
@@ -72,6 +72,7 @@ A list containing results from the ColocBoost analysis:
 with or without the outcomes of interest.
 }
 \details{
+When \code{summary_level = 1}, additional details and examples are introduced in \code{\link{get_cos_summary}}.
 When \code{summary_level = 2} or \code{summary_level = 3}, additional details for trait-specific effects and ambiguous
 colocalization events are included. See \code{\link{get_ucos_summary}} for details on these tables.
 }
diff --git a/man/get_ucos_summary.Rd b/man/get_ucos_summary.Rd
index 97cc419..71cd30c 100644
--- a/man/get_ucos_summary.Rd
+++ b/man/get_ucos_summary.Rd
@@ -12,7 +12,7 @@ get_ucos_summary(
   cb_output,
   outcome_names = NULL,
   region_name = NULL,
-  ambiguous_ucos = FALSE,
+  ambiguous_cos = FALSE,
   min_abs_corr_between_ucos = 0.5,
   median_abs_corr_between_ucos = 0.8
 )
@@ -24,7 +24,7 @@ get_ucos_summary(
 
 \item{region_name}{Optional character string. When provided, adds a column with this gene name to the output table for easier filtering in downstream analyses.}
 
-\item{ambiguous_ucos}{Logical indicating whether to include ambiguous colocalization events. The default is FALSE.}
+\item{ambiguous_cos}{Logical indicating whether to include ambiguous colocalization events. The default is FALSE.}
 
 \item{min_abs_corr_between_ucos}{Minimum absolute correlation for variants across two trait-specific (uncolocalized) effects to be considered colocalized. The default is 0.5.}
 
@@ -47,7 +47,7 @@ A list containing:
 \item \code{ucos_variables_vpa}: Variant-level probability of association (VPA) for all variables in the confidence set
 \item \code{region_name}: Region name if provided through the region_name parameter
 }
-\item \code{ambiguous_ucos_summary}: A summary table for ambiguous colocalization events with the following columns:
+\item \code{ambiguous_cos_summary}: A summary table for ambiguous colocalization events with the following columns:
 \itemize{
 \item \code{outcomes}: Outcome in the ambiguous colocalization event
 \item \code{ucos_id}: Unique identifiers for the ambiguous event
diff --git a/tests/testthat/test_corner_cases.R b/tests/testthat/test_corner_cases.R
index 0ba15bd..d499159 100644
--- a/tests/testthat/test_corner_cases.R
+++ b/tests/testthat/test_corner_cases.R
@@ -359,9 +359,9 @@ test_that("get_ambiguous_colocalization handles edge cases with correlation thre
   
   # Compare number of ambiguous events found with different thresholds
   # Generally expect: n_high_thresh <= n_default <= n_low_thresh
-  n_high <- length(result_high_thresh$ambigous_ucos)
-  n_default <- length(get_ambiguous_colocalization(test_colocboost_results)$ambigous_ucos)
-  n_low <- length(result_low_thresh$ambigous_ucos)
+  n_high <- length(result_high_thresh$ambiguous_cos)
+  n_default <- length(get_ambiguous_colocalization(test_colocboost_results)$ambiguous_cos)
+  n_low <- length(result_low_thresh$ambiguous_cos)
   
   # Higher thresholds should find equal or fewer ambiguities than default
   expect_true(n_high <= n_default)
@@ -385,7 +385,7 @@ test_that("get_ambiguous_colocalization handles edge cases with correlation thre
     min_abs_corr_between_ucos = 0.0,
     median_abs_corr_between_ucos = 0.0
   )
-  expect_true(length(result_zero$ambigous_ucos) >= n_low)
+  expect_true(length(result_zero$ambiguous_cos) >= n_low)
   
   
 })
diff --git a/tests/testthat/test_inference.R b/tests/testthat/test_inference.R
index 34a26a2..64e74f3 100644
--- a/tests/testthat/test_inference.R
+++ b/tests/testthat/test_inference.R
@@ -200,18 +200,18 @@ test_that("get_ambiguous_colocalization identifies ambiguous colocalizations cor
   # Check that the returned object is of class "colocboost"
   expect_s3_class(result, "colocboost")
   
-  # Check that the ambiguous_ucos field exists in the result
-  expect_true("ambigous_ucos" %in% names(result))
+  # Check that the ambiguous_cos field exists in the result
+  expect_true("ambiguous_cos" %in% names(result))
   
   # If ambiguous colocalizations were found, test their structure
-  if (length(result$ambigous_ucos) > 0) {
+  if (length(result$ambigous_cos) > 0) {
     # There should be fields for the ambiguous UCOs details
-    expect_true("ambigouse_ucos" %in% names(result$ambigous_ucos[[1]]))
-    expect_true("ambigouse_ucos_outcomes" %in% names(result$ambigous_ucos[[1]]))
-    expect_true("ambigous_ucos_weight" %in% names(result$ambigous_ucos[[1]]))
-    expect_true("ambigous_ucos_puriry" %in% names(result$ambigous_ucos[[1]]))
-    expect_true("ambigouse_ucos_union" %in% names(result$ambigous_ucos[[1]]))
-    expect_true("ambigouse_ucos_overlap" %in% names(result$ambigous_ucos[[1]]))
+    expect_true("ambiguous_cos" %in% names(result$ambigous_ucos[[1]]))
+    expect_true("ambiguous_cos_overlap" %in% names(result$ambigous_ucos[[1]]))
+    expect_true("ambiguous_cos_union" %in% names(result$ambigous_ucos[[1]]))
+    expect_true("ambiguous_cos_outcomes" %in% names(result$ambigous_ucos[[1]]))
+    expect_true("ambigous_cos_weight" %in% names(result$ambigous_ucos[[1]]))
+    expect_true("ambigous_cos_purity" %in% names(result$ambigous_ucos[[1]]))
     expect_true("recalibrated_cos_vcp" %in% names(result$ambigous_ucos[[1]]))
     expect_true("recalibrated_cos" %in% names(result$ambigous_ucos[[1]]))
   }
@@ -245,8 +245,8 @@ test_that("get_ambiguous_colocalization identifies ambiguous colocalizations cor
   # The result should be unchanged from the input
   expect_equal(result, cb_res)
   
-  # There should be no ambiguous_ucos field added
-  expect_false("ambigous_ucos" %in% names(result))
+  # There should be no ambiguous_cos field added
+  expect_false("ambigous_cos" %in% names(result))
 
 })
 
@@ -276,8 +276,8 @@ test_that("get_ucos_summary funtionality", {
   }
 
   # Basic call with default parameters
-  summary_ambiguous <- get_ucos_summary(test_colocboost_results, ambiguous_ucos = TRUE)
-  expect_true(all.equal(names(summary_ambiguous), c("ucos_summary", "ambiguous_ucos_summary")))
+  summary_ambiguous <- get_ucos_summary(test_colocboost_results, ambiguous_cos = TRUE)
+  expect_true(all.equal(names(summary_ambiguous), c("ucos_summary", "ambiguous_cos_summary")))
     
   # Check expected columns exist
   expected_cols <- c(
@@ -286,7 +286,7 @@ test_that("get_ucos_summary funtionality", {
     "recalibrated_index", "recalibrated_variables", "recalibrated_variables_vcp"
   )
   for (col in expected_cols) {
-    expect_true(col %in% colnames(summary_ambiguous$ambiguous_ucos_summary))
+    expect_true(col %in% colnames(summary_ambiguous$ambiguous_cos_summary))
   }
 
 })
@@ -355,7 +355,7 @@ test_that("get_colocboost_summary works correctly", {
                                     summary_level = 3, 
                                     min_abs_corr_between_ucos = 0.4,
                                     median_abs_corr_between_ucos = 0.7)
-  expect_named(summary3, c("cos_summary", "ucos_summary", "ambiguous_ucos_summary"))
+  expect_named(summary3, c("cos_summary", "ucos_summary", "ambiguous_cos_summary"))
   expect_s3_class(summary3$ucos_summary, "data.frame")
   
   # Test with interest_outcome
diff --git a/vignettes/Ambiguous_Colocalization.Rmd b/vignettes/Ambiguous_Colocalization.Rmd
index b056ac8..9dedb00 100644
--- a/vignettes/Ambiguous_Colocalization.Rmd
+++ b/vignettes/Ambiguous_Colocalization.Rmd
@@ -16,9 +16,8 @@ knitr::opts_chunk$set(
 
 
 This vignette demonstrates an example of ambiguous colocalization from trait-specific effects using the `colocboost`. 
-Specifically, we will use the `Ambiguous_Colocalization`, which is an example result from one of our real data applications, 
-showing an ambiguous colocalization between eQTL and GWAS.
-
+Specifically, we will use the `Ambiguous_Colocalization`, which is an example result from GTEx relsease v8 and UK Biobank summary statistics
+(see more details of data license in Acknowledgement section).
 
 ```{r setup}
 library(colocboost)
@@ -108,8 +107,8 @@ intersect(susie_eQTL$sets$cs$L1, susie_GWAS$sets$cs$L1)
 To visulize the fine-mapping results,
 
 ```{r plot-susie}
-susieR::susie_plot(susie_eQTL, y = "PIP")
-susieR::susie_plot(susie_GWAS, y = "PIP")
+susieR::susie_plot(susie_eQTL, y = "PIP", pos = 2000:n_variables)
+susieR::susie_plot(susie_GWAS, y = "PIP", pos = 2000:n_variables)
 ```
 
 
@@ -117,6 +116,8 @@ susieR::susie_plot(susie_GWAS, y = "PIP")
 
 ColocBoost provides a function to get the ambiguous colocalization results and summary from trait-specifc effects, by considering the correlation of variants between the two uCoS.
 
+## 3.1. Get the ambiguous colocalization results
+
 The `get_ambiguous_colocalization` function will return the ambiguous results in `ambigous_ucos` object, if the following conditions are met:
 
 - The two uCoS should have at least one overlapping variant.
@@ -126,11 +127,30 @@ The `get_ambiguous_colocalization` function will return the ambiguous results in
 
 ```{r ambiguous-results}
 colocboost_results <- Ambiguous_Colocalization$ColocBoost_Results
-res <- get_ambiguous_colocalization(colocboost_results, min_abs_corr_between_ucos = 0.5, median_abs_corr_between_ucos = 0.8)
+res <- get_ambiguous_colocalization(
+  colocboost_results, 
+  min_abs_corr_between_ucos = 0.5, 
+  median_abs_corr_between_ucos = 0.8
+)
 names(res)
-names(res$ambigous_ucos)
+names(res$ambiguous_cos)
+names(res$ambiguous_cos[[1]])
 ```
 
+**Explanation of results** For each ambiguous colocalization, the following information is provided:
+
+- `ambigous_cos`: Contains variants indices and names of the original trait-specific uCoS used to constuct this ambiguouse colocalization.
+- `ambigouse_cos_overlap`: Contains the overlapping variants information across the uCoS  used to constuct this ambiguouse colocalization.
+- `ambigouse_cos_union`: Contains the union of variants information across the uCoS used to constuct this ambiguouse colocalization.
+- `ambigouse_cos_outcomes`: Contains the outcomes indicies and names for uCoS used to constuct this ambiguouse colocalization.
+- `ambigous_cos_weight`: Contains the trait-specific weights of the uCoS used to constuct this ambiguouse colocalization.
+- `ambigous_cos_puriry`: Contains the purity of across uCoS used to constuct this ambiguouse colocalization.
+- `recalibrated_cos_vcp`: Contains the recalibrated integrative weight to analogous to variant colocalization probability (VCP) from the ambiguous colocalization results.
+- `recalibrated_cos`: Contains the recalibrated 95% colocalization confidence set (CoS) from the ambiguous colocalization results.
+
+
+## 3.2. Get the summary of ambiguous colocalization results
+
 To get the summary of ambiguous colocalization results, we can use the `get_colocboost_summary` function.
 
 - `summary_level = 1` (default): get the summary table for only the colocalization results, same as `cos_summary` in ColocBoost output.
@@ -143,11 +163,33 @@ full_summary <- get_colocboost_summary(colocboost_results, summary_level = 3)
 names(full_summary)
 
 # Get the summary of ambiguous colocalization results
-summary_ambiguous <- full_summary$ambiguous_ucos_summary
+summary_ambiguous <- full_summary$ambiguous_cos_summary
 colnames(summary_ambiguous)
 ```
 
-
 - `recalibrated_*`: giving the recalibrated weigths and recalibrated 95% colocalization confidece sets (CoS) from the trait-specific effects.
 
-See details of function usage in the [Functions](https://statfungen.github.io/colocboost/reference/index.html).
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+See details of function usage in the [Functions](https://statfungen.github.io/colocboost/reference/index.html).
+
+
+
+# 4. Take home message
+
+In this vignette, we have demonstrated how the post-processing of ColocBoost results to handle ambiguous colocalization scenarios 
+where trait-specific effects share overlapping variants with high correlation. 
+
+- Through empirical studies, we have found that the minimum absolute correlation cutoff of 0.5 and median absolute correlation cutoff of 0.8 produce reasonable results 
+when merging two uCoS. We recommend users not to lower these thresholds further without strong justification. 
+- While we provide recalibrated weights as a suggested approach for interpreting ambiguous results, 
+users can still choose between recalibrated weights and trait-specific weights based on their research context. 
+- This ambiguity typically arises when some trait-specific boosting learners are updating very similar sets of variants, 
+leading to substantial correlation between what initially appear to be separate signals. 
+
+By properly identifying and quantifying this ambiguity, users can gain a more nuanced understanding of the underlying genetic architecture of the traits they are studying.
+
+
+# Acknowledgements
+
+- The eQTL data used for the analyses described in this example results were obtained from GTEx release v8 from [GTEx Portal](https://gtexportal.org/home/downloads/adult-gtex/qtl).
+- The GWAS summary statistics used for the analyses described in this example results were obtained from UK Biobank (UKBB) 
+from [UK Biobank](https://www.ukbiobank.ac.uk/) and downloaded from [Nealelab](https://www.nealelab.is/uk-biobank).
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