--- a
+++ b/R/PathwayCount.R
@@ -0,0 +1,51 @@
+#' Count Genes Present in Pathways Above a Threshold
+#'
+#' This function filters pathways that meet a count threshold and then counts the presence of specified genes in those pathways.
+#'
+#' @importFrom dplyr filter
+#' @importFrom rlang .data
+#' @param GO A character vector of gene symbols.
+#' @param count_threshold An integer specifying the count threshold for selecting pathways.
+#' @param enrich_data A data frame containing pathway enrichment analysis results.
+#' @return A data frame with columns "Symble" (gene symbol), "Description" (pathway description), and "Exists" (1 if gene is present, 0 otherwise).
+#' @export
+#'
+#' @examples
+#' # Simulated gene list
+#' GO <- c("Gene1", "Gene2", "Gene3", "Gene4", "Gene5")
+#' # Simulated enrichment analysis data
+#' enrich_data <- data.frame(
+#'   ID = c("GO:0001", "GO:0002", "GO:0003"),
+#'   Description = c("Pathway A", "Pathway B", "Pathway C"),
+#'   Count = c(10, 4, 6),
+#'   geneID = c("Gene1/Gene2/Gene3", "Gene4/Gene5", "Gene2/Gene6/Gene7")
+#' )
+#'
+#' # Example usage
+#' count_threshold <- 5
+#' result_df <- pathway_count(GO, count_threshold, enrich_data)
+#'
+pathway_count <- function(GO, count_threshold, enrich_data) {
+  # Filter pathways meeting the count threshold
+  selected_pathways <- enrich_data %>%
+    dplyr::filter(.data$Count > count_threshold)
+
+  final_df <- data.frame(Symble = character(), Description = character(), Exists = integer())
+
+  # Iterate through each selected pathway
+  for (i in 1:nrow(selected_pathways)) {
+    pathway_info <- selected_pathways[i, ]
+    genes_in_pathway <- unlist(strsplit(as.character(pathway_info$geneID), "/"))
+
+    # Create a record for each gene in the current pathway
+    for (gene in GO) {
+      final_df <- rbind(final_df, data.frame(
+        Symble = gene,
+        Description = pathway_info$Description,
+        Exists = as.integer(gene %in% genes_in_pathway)
+      ))
+    }
+  }
+
+  return(final_df)
+}