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#' Describe Genes Present in Selected Pathways
#'
#' This function identifies genes present in selected pathways based on gene enrichment analysis results.
#'
#' @importFrom dplyr filter
#' @importFrom rlang .data
#' @param GO A character vector of gene symbols.
#' @param selected_pathways_names A character vector specifying the names of selected 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
#' GO <- c("Gene1", "Gene2", "Gene3", "Gene4", "Gene5")
#' # Simulated enrichment analysis data
#' enrich_data <- data.frame(
#' ID = c("Pathway1", "Pathway2", "Pathway3", "Pathway4"),
#' Description = c("Apoptosis", "Cell Cycle", "Signal Transduction", "Metabolism"),
#' geneID = c("Gene1/Gene3", "Gene2/Gene4", "Gene1/Gene2/Gene3", "Gene5"),
#' Count = c(2, 2, 3, 1),
#' stringsAsFactors = FALSE
#' )
#'
#' # Example usage
#' result <- pathway_description(GO,
#' selected_pathways_names="Apoptosis",
#' enrich_data)
#'
pathway_description <- function(GO, selected_pathways_names, enrich_data) {
# Filter selected pathways
selected_pathways <- dplyr::filter(enrich_data, .data$Description %in% selected_pathways_names)
final_df <- data.frame(Symble = character(), Description = character(), Exists = integer())
# Iterate through each selected pathway
for (i in 1:nrow(selected_pathways)) {
pathway_info <- selected_pathways[i, ]
genes_in_pathway <- unlist(strsplit(as.character(pathway_info$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)
}
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