diff --git a/R/ae_forestly.R b/R/ae_forestly.R
index 7896520..d59b1a9 100644
--- a/R/ae_forestly.R
+++ b/R/ae_forestly.R
@@ -44,7 +44,6 @@
 #'     format_ae_forestly() |>
 #'     ae_forestly()
 #' }
-
 ae_forestly <- function(outdata,
                         display_soc_toggle = TRUE,
                         filter = c("prop", "n"),
@@ -90,8 +89,9 @@ ae_forestly <- function(outdata,
 
   if (is.null(filter_label)) {
     filter_label <- ifelse(filter == "prop",
-                           "Incidence (%) in One or More Treatment Groups",
-                           "Number of AE in One or More Treatment Groups")
+      "Incidence (%) in One or More Treatment Groups",
+      "Number of AE in One or More Treatment Groups"
+    )
   }
 
   # `max_page` controls the maximum page number displayed in the interactive forest table.
@@ -108,13 +108,15 @@ ae_forestly <- function(outdata,
     FUN.VALUE = character(1)
   )
 
-  for (par in parameters[(!(parameters %in% unique(outdata$parameter_order)))]){
+  for (par in parameters[(!(parameters %in% unique(outdata$parameter_order)))]) {
     outdata$tbl <-
       rbind(outdata$tbl, NA)
     outdata$tbl$name <- ifelse(is.na(outdata$tbl$name), "No data to display", outdata$tbl$name)
     outdata$tbl$parameter <-
-      factor(ifelse(is.na(outdata$tbl$parameter), par, as.character(outdata$tbl$parameter)),
-             levels(outdata$parameter_order))
+      factor(
+        ifelse(is.na(outdata$tbl$parameter), par, as.character(outdata$tbl$parameter)),
+        levels(outdata$parameter_order)
+      )
   }
 
   outdata$tbl$parameter <- factor(
@@ -191,8 +193,8 @@ ae_forestly <- function(outdata,
         outdata$ae_listing,
         ((toupper(outdata$ae_listing$Adverse_Event) %in% toupper(t_row)) &
           (outdata$ae_listing$param == t_param)) |
-        ((toupper(outdata$ae_listing$SOC_Name) %in% toupper(t_row)) &
-           (outdata$ae_listing$param == t_param))
+          ((toupper(outdata$ae_listing$SOC_Name) %in% toupper(t_row)) &
+            (outdata$ae_listing$param == t_param))
       )
 
       # Exclude 'param' column from t_details
@@ -217,9 +219,9 @@ ae_forestly <- function(outdata,
       col_defs <- stats::setNames(
         lapply(names(t_details), function(name) {
           # Use label from the list
-          label_name <- if(is.null(labels[[name]])) name else labels[[name]][[1]]
+          label_name <- if (is.null(labels[[name]])) name else labels[[name]][[1]]
           reactable::colDef(
-            header = label_name,  # Use header instead of name
+            header = label_name, # Use header instead of name
             cell = function(value) format(value, nsmall = 1),
             align = "center",
             minWidth = 70
@@ -242,7 +244,6 @@ ae_forestly <- function(outdata,
         highlight = TRUE
       )
     },
-
     pageSizeOptions = max_page,
 
     # Default sort variable
diff --git a/R/ae_listing.R b/R/ae_listing.R
index f3ef362..02432fe 100644
--- a/R/ae_listing.R
+++ b/R/ae_listing.R
@@ -208,9 +208,9 @@ format_ae_listing <- function(outdata, display_unique_records = FALSE) {
   }
   attr(res[["Participant_ID"]], "label") <- NULL
 
-  res[["Gender"]] <- titlecase(res[["SEX"]])
+  res[["Gender"]] <- tools::toTitleCase(res[["SEX"]])
 
-  res[["Race"]] <- titlecase(res[["RACE"]])
+  res[["Race"]] <- tools::toTitleCase(tolower(res[["RACE"]]))
 
   res[["Age"]] <- res[["AGE"]]
 
@@ -220,10 +220,9 @@ format_ae_listing <- function(outdata, display_unique_records = FALSE) {
 
   # Onset epoch
   if ("EPOCH" %in% toupper(names(res))) {
-    res[["Onset_Epoch"]] <- titlecase(res[["EPOCH"]])
+    res[["Onset_Epoch"]] <- tools::toTitleCase(tolower(res[["EPOCH"]])) # propcase the EPOCH
   }
 
-
   # Relative day of onset (ASTDY)
   if ("ASTDY" %in% toupper(names(res))) {
     res[["Relative_Day_of_Onset"]] <- res[["ASTDY"]]
@@ -239,7 +238,7 @@ format_ae_listing <- function(outdata, display_unique_records = FALSE) {
   # Duration
   if ("ADURN" %in% toupper(names(res)) & "ADURU" %in% toupper(names(res))) {
     res[["Duration"]] <- paste(ifelse(is.na(res[["ADURN"]]), "", as.character(res[["ADURN"]])),
-      titlecase(res[["ADURU"]]),
+      tools::toTitleCase(tolower(res[["ADURU"]])),
       sep = " "
     ) # AE duration with unit
 
@@ -275,7 +274,7 @@ format_ae_listing <- function(outdata, display_unique_records = FALSE) {
   # AE related
   if ("AEREL" %in% toupper(names(res))) {
     res[["Related"]] <- ifelse(res[["AEREL"]] == "RELATED", "Y", ifelse(
-      toupper(res[["AEREL"]]) == "NOT RELATED", "N", titlecase(res[["AEREL"]])
+      toupper(res[["AEREL"]]) == "NOT RELATED", "N", tools::toTitleCase(tolower(res[["AEREL"]]))
     ))
   }
 
@@ -290,7 +289,7 @@ format_ae_listing <- function(outdata, display_unique_records = FALSE) {
           "DOSE INCREASED" = "Increased",
           "NOT APPLICABLE" = "N/A",
           "UNKNOWN" = "Unknown",
-          titlecase(res[["AEACN"]][i])
+          tools::toTitleCase(tolower(res[["AEACN"]][i]))
         )
       }
     } else {
@@ -307,7 +306,7 @@ format_ae_listing <- function(outdata, display_unique_records = FALSE) {
           "RECOVERING/RESOLVING" = "Resolving",
           "RECOVERED/RESOLVED WITH SEQUELAE" = "Sequelae",
           "NOT RECOVERED/NOT RESOLVED" = "Not Resolved",
-          titlecase(res[["AEOUT"]][i])
+          tools::toTitleCase(tolower(res[["AEOUT"]][i]))
         )
       }
     } else {
diff --git a/R/format_ae_forestly.R b/R/format_ae_forestly.R
index 17157d9..dc1fff9 100644
--- a/R/format_ae_forestly.R
+++ b/R/format_ae_forestly.R
@@ -50,13 +50,13 @@
 #' @export
 #'
 #' @examples
-#' adsl <- forestly_adsl[1:100,]
-#' adae <- forestly_adae[1:100,]
+#' adsl <- forestly_adsl[1:100, ]
+#' adae <- forestly_adae[1:100, ]
 #' meta_forestly(
 #'   dataset_adsl = adsl,
 #'   dataset_adae = adae
 #' ) |>
-#'   prepare_ae_forestly()|>
+#'   prepare_ae_forestly() |>
 #'   format_ae_forestly()
 format_ae_forestly <- function(
     outdata,
@@ -158,7 +158,7 @@ format_ae_forestly <- function(
     fig_prop_range <- round(range(tbl_prop, na.rm = TRUE) + c(-2, 2))
   } else {
     if (prop_range[1] > range(tbl_prop, na.rm = TRUE)[1] |
-        prop_range[2] < range(tbl_prop, na.rm = TRUE)[2]) {
+      prop_range[2] < range(tbl_prop, na.rm = TRUE)[2]) {
       warning("There are data points outside the specified range for proportion.")
     }
     fig_prop_range <- prop_range
@@ -204,7 +204,7 @@ format_ae_forestly <- function(
     fig_diff_range <- round(range(tbl_diff, na.rm = TRUE) + c(-2, 2))
   } else {
     if (diff_range[1] > range(tbl_diff, na.rm = TRUE)[1] |
-        diff_range[2] < range(tbl_diff, na.rm = TRUE)[2]) {
+      diff_range[2] < range(tbl_diff, na.rm = TRUE)[2]) {
       warning("There are data points outside the specified range for difference.")
     }
     fig_diff_range <- diff_range
@@ -369,14 +369,16 @@ format_ae_forestly <- function(
   )
 
   # column hidden
-  columns <- lapply(columns, function (x) {
+  columns <- lapply(columns, function(x) {
     if (!"show" %in% names(x)) {
       x$show <- TRUE
     }
     return(x)
   })
 
-  hidden_item <- names(columns)[(!names(columns) %in% "soc_name") & (sapply(columns, function(x) {return(!x$show)}))]
+  hidden_item <- names(columns)[(!names(columns) %in% "soc_name") & (sapply(columns, function(x) {
+    return(!x$show)
+  }))]
 
   # Create outdata
   outdata$tbl <- tbl
diff --git a/R/prepare_ae_forestly.R b/R/prepare_ae_forestly.R
index e3a1777..6b40968 100644
--- a/R/prepare_ae_forestly.R
+++ b/R/prepare_ae_forestly.R
@@ -29,8 +29,8 @@
 #' @export
 #'
 #' @examples
-#' adsl <- forestly_adsl[1:100,]
-#' adae <- forestly_adae[1:100,]
+#' adsl <- forestly_adsl[1:100, ]
+#' adae <- forestly_adae[1:100, ]
 #' meta_forestly(
 #'   dataset_adsl = adsl,
 #'   dataset_adae = adae
@@ -48,8 +48,6 @@ prepare_ae_forestly <- function(
       "AEREL", "AEACN", "AEOUT", "ADURN", "ADURU"
     ),
     ae_listing_unique = FALSE) {
-
-
   if (is.null(population)) {
     if (length(meta$population) == 1) {
       population <- meta$population[[1]]$name
@@ -66,32 +64,32 @@ prepare_ae_forestly <- function(
     }
   }
 
-  if( is.null(parameter)){
+  if (is.null(parameter)) {
     parameters <- names(meta$parameter)
 
     meta$parameter
-  }else{
+  } else {
     parameters <- unlist(strsplit(parameter, ";"))
   }
 
-  for(i in seq_along(parameters)){
+  for (i in seq_along(parameters)) {
     para <- meta$parameter[[parameters[i]]]
-    if(is.null(para$var)){
+    if (is.null(para$var)) {
       para$var <- "AEDECOD"
     }
-    if(is.null(para$soc)){
+    if (is.null(para$soc)) {
       para$soc <- "AEBODSYS"
     }
-    if(is.null(para$seq)){
+    if (is.null(para$seq)) {
       para$seq <- sample(1e5:2e5, size = 1)
     }
-    if(is.null(para$term1)){
+    if (is.null(para$term1)) {
       para$term1 <- ""
     }
-    if(is.null(para$term2)){
+    if (is.null(para$term2)) {
       para$term2 <- ""
     }
-    if(is.null(para$summ_row)){
+    if (is.null(para$summ_row)) {
       para$summ_row <- ""
     }
     meta$parameter[[parameters[i]]] <- para
@@ -112,7 +110,7 @@ prepare_ae_forestly <- function(
 
   ae_listing <- data.frame()
   for (i in 1:length(res)) {
-    if (nrow(res[[i]]$ae_listing) > 0){
+    if (nrow(res[[i]]$ae_listing) > 0) {
       res[[i]]$ae_listing$param <- res[[i]]$parameter
       ae_listing <- rbind(ae_listing, res[[i]]$ae_listing)
     }
@@ -151,10 +149,12 @@ prepare_ae_forestly <- function(
   parameter_order <- factor(parameter_order, levels = parameters)
 
   # Display message if a specified-parameter is not included
-  if (any(!(parameters %in% unique(parameter_order)))){
-    warning(paste0('There is no record for the parameter "',
-                   parameters[!(parameters %in% unique(parameter_order))],
-                   '" to display.'))
+  if (any(!(parameters %in% unique(parameter_order)))) {
+    warning(paste0(
+      'There is no record for the parameter "',
+      parameters[!(parameters %in% unique(parameter_order))],
+      '" to display.'
+    ))
   }
 
   # Additional group information
diff --git a/R/reactable2.R b/R/reactable2.R
index a91b39e..dc03c38 100644
--- a/R/reactable2.R
+++ b/R/reactable2.R
@@ -111,16 +111,18 @@ reactable2 <- function(
   )
 
   if (soc_toggle) {
-    on_click2 <- paste0("function control_column(hidden_columns) {",
-                        "  if (hidden_columns.includes('soc_name')) {",
-                        "    Reactable.setHiddenColumns('", element_id, "', prevColumns => {
-                             return prevColumns.length === 0 ? ['soc_name']:[", hidden_item ,"]})",
-                        "  } else {",
-                        "    Reactable.setHiddenColumns('", element_id, "', prevColumns => {
-                             return prevColumns.length === 0 ? [ ]: ['soc_name',",  hidden_item, "]})",
-                        "  }",
-                        "}",
-                        "control_column(Reactable.getState('", element_id, "').hiddenColumns);")
+    on_click2 <- paste0(
+      "function control_column(hidden_columns) {",
+      "  if (hidden_columns.includes('soc_name')) {",
+      "    Reactable.setHiddenColumns('", element_id, "', prevColumns => {
+                             return prevColumns.length === 0 ? ['soc_name']:[", hidden_item, "]})",
+      "  } else {",
+      "    Reactable.setHiddenColumns('", element_id, "', prevColumns => {
+                             return prevColumns.length === 0 ? [ ]: ['soc_name',", hidden_item, "]})",
+      "  }",
+      "}",
+      "control_column(Reactable.getState('", element_id, "').hiddenColumns);"
+    )
 
     tbl <- htmltools::tagList(
       htmltools::tags$button(
diff --git a/data-raw/forestly_adae.R b/data-raw/forestly_adae.R
index c3b2efe..ceeed0a 100644
--- a/data-raw/forestly_adae.R
+++ b/data-raw/forestly_adae.R
@@ -9,19 +9,22 @@ adae <- r2rtf::r2rtf_adae
 
 
 # Derive AREL from existing AEREL
-adae <- adae %>% filter(TRTA!="Xanomeline High Dose") %>%
+adae <- adae %>%
+  filter(TRTA != "Xanomeline High Dose") %>%
   mutate(AREL = case_when(
     AEREL %in% c("PROBABLE", "POSSIBLE") ~ "RELATED",
     AEREL %in% c("NONE", "REMOTE", "") ~ "NOT RELATED",
-    TRUE ~ AEREL  # Keep original AREL if none of the conditions are met
+    TRUE ~ AEREL # Keep original AREL if none of the conditions are met
   ))
 
 
-freq <- adae %>% count(AREL, AEREL) %>%
+freq <- adae %>%
+  count(AREL, AEREL) %>%
   arrange(desc(n))
 print(freq)
 
-freq2 <- forestly_adae %>% count(AREL, AEREL) %>%
+freq2 <- forestly_adae %>%
+  count(AREL, AEREL) %>%
   arrange(desc(n))
 print(freq2)
 
@@ -39,17 +42,17 @@ adae$AEACN <- sample(
 
 for (i in seq_along(adae$AEACN)) {
   adae$action_taken[i] <- switch(adae$AEACN[i],
-                                 "DOSE NOT CHANGED" = "None",
-                                 "DRUG INTERRUPTED" = "Interrupted",
-                                 "DRUG WITHDRAWN" = "Discontinued",
-                                 "NOT APPLICABLE" = "N/A",
-                                 "UNKNOWN" = "Unknown",
-                                 "''" = "None",
-                                 tools::toTitleCase(tolower(adae$AEACN[i]))
+    "DOSE NOT CHANGED" = "None",
+    "DRUG INTERRUPTED" = "Interrupted",
+    "DRUG WITHDRAWN" = "Discontinued",
+    "NOT APPLICABLE" = "N/A",
+    "UNKNOWN" = "Unknown",
+    "''" = "None",
+    tools::toTitleCase(tolower(adae$AEACN[i]))
   )
 }
 
-#CHECKS
+# CHECKS
 # freq <- adae %>% count(AEACN) %>% arrange(desc(n))
 # print(freq)
 #
diff --git a/man/format_ae_forestly.Rd b/man/format_ae_forestly.Rd
index 2d44845..77850ba 100644
--- a/man/format_ae_forestly.Rd
+++ b/man/format_ae_forestly.Rd
@@ -75,12 +75,12 @@ An \code{outdata} object.
 Format outdata for interactive forest plot
 }
 \examples{
-adsl <- forestly_adsl[1:100,]
-adae <- forestly_adae[1:100,]
+adsl <- forestly_adsl[1:100, ]
+adae <- forestly_adae[1:100, ]
 meta_forestly(
   dataset_adsl = adsl,
   dataset_adae = adae
 ) |>
-  prepare_ae_forestly()|>
+  prepare_ae_forestly() |>
   format_ae_forestly()
 }
diff --git a/man/prepare_ae_forestly.Rd b/man/prepare_ae_forestly.Rd
index aa286aa..b6bafc5 100644
--- a/man/prepare_ae_forestly.Rd
+++ b/man/prepare_ae_forestly.Rd
@@ -46,8 +46,8 @@ An \code{outdata} object.
 Prepare datasets for interactive forest plot
 }
 \examples{
-adsl <- forestly_adsl[1:100,]
-adae <- forestly_adae[1:100,]
+adsl <- forestly_adsl[1:100, ]
+adae <- forestly_adae[1:100, ]
 meta_forestly(
   dataset_adsl = adsl,
   dataset_adae = adae
diff --git a/vignettes/customize-ae-specific-columns.Rmd b/vignettes/customize-ae-specific-columns.Rmd
index 703efbf..1f03c5c 100644
--- a/vignettes/customize-ae-specific-columns.Rmd
+++ b/vignettes/customize-ae-specific-columns.Rmd
@@ -43,31 +43,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -92,4 +104,4 @@ meta |>
   prepare_ae_forestly() |>
   format_ae_forestly(display = c("n", "prop", "fig_prop", "fig_diff", "total")) |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/customize-color.Rmd b/vignettes/customize-color.Rmd
index ba149a7..0311dd9 100644
--- a/vignettes/customize-color.Rmd
+++ b/vignettes/customize-color.Rmd
@@ -36,31 +36,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -76,4 +88,4 @@ meta |>
   prepare_ae_forestly() |>
   format_ae_forestly(color = c("black", "grey60", "grey40")) |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/customize-diff-label.Rmd b/vignettes/customize-diff-label.Rmd
index 455ba1e..30918ef 100644
--- a/vignettes/customize-diff-label.Rmd
+++ b/vignettes/customize-diff-label.Rmd
@@ -36,31 +36,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -74,6 +86,6 @@ In the example below, we show how to change the legend text. We encourage users
 ```{r}
 meta |>
   prepare_ae_forestly() |>
-  format_ae_forestly(diff_label = "New Drug <- Favor -> SoC",) |>
+  format_ae_forestly(diff_label = "New Drug <- Favor -> SoC", ) |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/customize-digits.Rmd b/vignettes/customize-digits.Rmd
index 5a748c2..c14353e 100644
--- a/vignettes/customize-digits.Rmd
+++ b/vignettes/customize-digits.Rmd
@@ -36,31 +36,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -74,4 +86,4 @@ meta |>
   prepare_ae_forestly() |>
   format_ae_forestly(digits = 2) |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/customize-listing-columns.Rmd b/vignettes/customize-listing-columns.Rmd
index 4df780d..1786f49 100644
--- a/vignettes/customize-listing-columns.Rmd
+++ b/vignettes/customize-listing-columns.Rmd
@@ -38,31 +38,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -77,4 +89,4 @@ meta |>
   prepare_ae_forestly(ae_listing_display = c("USUBJID", "SITEID", "SEX", "RACE", "AGE")) |>
   format_ae_forestly() |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/customize-width.Rmd b/vignettes/customize-width.Rmd
index 4e7de68..a39b333 100644
--- a/vignettes/customize-width.Rmd
+++ b/vignettes/customize-width.Rmd
@@ -36,31 +36,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -81,14 +93,16 @@ In the example below, we modify the column widths to better suit the display. Us
 ```{r}
 meta |>
   prepare_ae_forestly() |>
-  format_ae_forestly(width_term = 5, # width of the column of AE PT term
-                     # widths of the column of subject with AE counts
-                     width_n = 2, 
-                     # widths of the column of AE proportions
-                     width_prop = 2, 
-                     # widths of plotting the AE proportions and differences
-                     width_fig = 150, 
-                     # vertical space between legend and the table
-                     footer_space = 100) |>
+  format_ae_forestly(
+    width_term = 5, # width of the column of AE PT term
+    # widths of the column of subject with AE counts
+    width_n = 2,
+    # widths of the column of AE proportions
+    width_prop = 2,
+    # widths of plotting the AE proportions and differences
+    width_fig = 150,
+    # vertical space between legend and the table
+    footer_space = 100
+  ) |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/customize-xlimit.Rmd b/vignettes/customize-xlimit.Rmd
index d767b0a..4af5a6f 100644
--- a/vignettes/customize-xlimit.Rmd
+++ b/vignettes/customize-xlimit.Rmd
@@ -36,31 +36,43 @@ Building interactive AE forest plots starts with constructing the metadata. The
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 
 meta <- meta_adam(population = adsl, observation = adae) |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related")) |>
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related"
+  )) |>
   define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>  
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
   meta_build()
 ```
 
@@ -78,4 +90,4 @@ meta |>
   prepare_ae_forestly() |>
   format_ae_forestly(prop_range = c(-0.5, 30), diff_range = c(-10, 35)) |>
   ae_forestly()
-```
\ No newline at end of file
+```
diff --git a/vignettes/forestly.Rmd b/vignettes/forestly.Rmd
index d9087b8..8172b0c 100644
--- a/vignettes/forestly.Rmd
+++ b/vignettes/forestly.Rmd
@@ -48,12 +48,14 @@ library(forestly)
 adsl <- forestly_adsl
 adae <- forestly_adae
 
-adsl$TRTA <- factor(forestly_adsl$TRT01A, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
-adae$TRTA <- factor(forestly_adae$TRTA, 
-                    levels = c("Xanomeline Low Dose", "Placebo"), 
-                    labels = c("Low Dose", "Placebo"))
+adsl$TRTA <- factor(forestly_adsl$TRT01A,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
+adae$TRTA <- factor(forestly_adae$TRTA,
+  levels = c("Xanomeline Low Dose", "Placebo"),
+  labels = c("Low Dose", "Placebo")
+)
 ```
 
 ## Step 2: build the metadata
@@ -74,59 +76,73 @@ Without loss of generality, our plan is to generate the following four AE-specif
 However, users are allowed to add more AE-specific tables as needed. For the above 4 AE specific tables, we take the APaT for both observation and observation. 
 ```{r}
 meta <- meta |>
-  define_plan(plan = plan(analysis = "ae_forestly", 
-                          population = "apat",
-                          observation = "apat", 
-                          parameter = "any;drug-related;serious;drug-related-serious")) 
+  define_plan(plan = plan(
+    analysis = "ae_forestly",
+    population = "apat",
+    observation = "apat",
+    parameter = "any;drug-related;serious;drug-related-serious"
+  ))
 ```
 
 Following the definition of the analysis plan, we further specify the details of `analysis = "ae_forestly"` by providing its label for display.
 ```{r}
 meta <- meta |>
-  define_analysis(name = "ae_forestly", label = "Interactive Forest Plot") 
+  define_analysis(name = "ae_forestly", label = "Interactive Forest Plot")
 ```
 
 We then define the related population (`population = "apat"`) and observation (`observation = "apat"`) by specifying their grouping variable (`group = ...`), subject ID (`id = ...`), population flag (`subset = ...`) and label (`label = ...`). If users wish to use different population flags, grouping variables, or labels, they can make changes as needed.
 ```{r}
 meta <- meta |>
-  define_population(name = "apat", group = "TRTA", id = "USUBJID",
-                    subset = SAFFL == "Y", label = "All Patient as Treated") |>
-  define_observation(name = "apat", group = "TRTA", 
-                     subset = SAFFL == "Y", label = "All Patient as Treated") 
+  define_population(
+    name = "apat", group = "TRTA", id = "USUBJID",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  ) |>
+  define_observation(
+    name = "apat", group = "TRTA",
+    subset = SAFFL == "Y", label = "All Patient as Treated"
+  )
 ```
 
 Next, we specify the details of `parameter = "any;drug-related;serious;drug-related-serious"`. For any AEs (`"any"`), their is no filter applied. 
 ```{r}
 meta <- meta |>
-  define_parameter(name = "any", 
-                   subset = NULL,
-                   label = "Any AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS")
+  define_parameter(
+    name = "any",
+    subset = NULL,
+    label = "Any AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  )
 ```
 For drug related AEs (`"drug-related"`), its filter is `AEREL %in% c("PROBABLE", "POSSIBLE")`.
 ```{r}
 meta <- meta |>
-  define_parameter(name = "drug-related", 
-                   subset = toupper(AREL) == "RELATED",
-                   label = "Drug-related AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") 
+  define_parameter(
+    name = "drug-related",
+    subset = toupper(AREL) == "RELATED",
+    label = "Drug-related AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  )
 ```
 Similarly, we define serious AE and drug related serious AEs.
 ```{r}
 meta <- meta |>
-  define_parameter(name = "serious", 
-                   subset = AESER == "Y",
-                   label = "Serious AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") |>
-  define_parameter(name = "drug-related-serious", 
-                   subset = AESER == "Y" & AEREL %in% c("PROBABLE", "POSSIBLE"),
-                   label = "Drug-related serious AEs", 
-                   var = "AEDECOD", soc = "AEBODSYS") 
+  define_parameter(
+    name = "serious",
+    subset = AESER == "Y",
+    label = "Serious AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  ) |>
+  define_parameter(
+    name = "drug-related-serious",
+    subset = AESER == "Y" & AEREL %in% c("PROBABLE", "POSSIBLE"),
+    label = "Drug-related serious AEs",
+    var = "AEDECOD", soc = "AEBODSYS"
+  )
 ```
 
 Finally, we build the metadata by running the `meta_build()` function.
 ```{r}
-meta <- meta |>  meta_build()
+meta <- meta |> meta_build()
 ```
 
 ## Step 3: generate the interative AE forest plot