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+#' Process Heatmap Data with Various Selection Options
+#'
+#' This function processes heatmap data (`heatdata`) based on a given selection option.
+#' It allows customization of column names, selection of specific columns per group,
+#' or averaging columns based on a common prefix.
+#'
+#' @param heatdata A data frame containing the heatmap data.
+#' @param selection An integer specifying the processing method:
+#' - 1: Use custom names for columns.
+#' - 2: Select a given number of columns per group based on a prefix.
+#' - 3: Calculate the average of columns per group based on a prefix.
+#' @param custom_names A character vector of custom names for columns (used when `selection = 1`).
+#' The length of this vector must match the number of columns in `heatdata`.
+#' @param num_names_per_group An integer specifying the number of columns to select per group (used when `selection = 2`).
+#' @param prefix_length An integer specifying the length of the prefix for grouping columns (used when `selection = 2` or `selection = 3`).
+#' Default is 4.
+#' @return A processed data frame based on the specified selection option.
+#' @export
+#'
+#' @examples
+#' # Example heatmap data frame
+#' heatdata <- data.frame(
+#'   groupA_1 = c(1, 2, 3),
+#'   groupA_2 = c(4, 5, 6),
+#'   groupB_1 = c(7, 8, 9),
+#'   groupB_2 = c(10, 11, 12)
+#' )
+#'
+#' # Selection 1: Use custom names for columns
+#' custom_names <- c("Sample1", "Sample2", "Sample3", "Sample4")
+#' processed_data1 <- process_heatdata(heatdata, selection = 1, custom_names = custom_names)
+#'
+#' # Selection 2: Select a given number of columns per group based on a prefix
+#' processed_data2 <- process_heatdata(heatdata, selection = 2, num_names_per_group = 1)
+#'
+#' # Selection 3: Calculate the average of columns per group based on a prefix
+#' processed_data3 <- process_heatdata(heatdata, selection = 3, prefix_length = 6)
+
+process_heatdata <- function(heatdata,
+                             selection = 1,
+                             custom_names = NULL,
+                             num_names_per_group = NULL,
+                             prefix_length = 4) {
+
+  if (selection == 1) {
+    # Option 1: Use custom names for columns
+    if (length(custom_names) != ncol(heatdata)) {
+      stop("Length of custom_names must match number of columns in heatdata")
+    }
+    names(heatdata) <- custom_names
+  } else if (selection == 2) {
+    # Option 2: Select a given number of columns per group based on a prefix
+    group_names <- unique(substr(names(heatdata), 1, prefix_length))  # Get unique group names based on prefix
+    selected_columns <- integer(0)
+    new_names <- character(0)
+
+    for (group in group_names) {
+      group_cols <- grep(group, names(heatdata))  # Find columns for each group
+      num_selected <- min(length(group_cols), num_names_per_group)
+      selected_columns <- c(selected_columns, sample(group_cols, num_selected))
+
+      # Generate new names for selected columns
+      new_group_names <- paste(group, seq_len(num_selected), sep = "_")
+      new_names <- c(new_names, new_group_names)
+    }
+
+    heatdata <- heatdata[, selected_columns, drop = FALSE]  # Keep only selected columns
+    names(heatdata) <- new_names
+  } else if (selection == 3) {
+    # Option 3: Calculate the average of columns per group based on a prefix
+    group_names <- unique(substr(names(heatdata), 1, prefix_length))
+
+    # Create a list to collect mean values for each group
+    mean_list <- list()
+
+    # Calculate mean values for each group and store them in the list
+    for (group in group_names) {
+      group_cols <- grep(group, names(heatdata), value = TRUE)
+      mean_list[[paste(group, "mean", sep = "_")]] <- rowMeans(heatdata[, group_cols], na.rm = TRUE)
+    }
+
+    # Convert list to data frame and set row names
+    heatdata <- as.data.frame(do.call(cbind, mean_list))
+    rownames(heatdata) <- rownames(heatdata)
+  } else {
+    stop("Invalid selection parameter")
+  }
+
+  return(heatdata)
+}