rm (list = ls ()) #清除所有变量
library(KEGGREST)# 设置工作目录并读取数据
setwd("C:\\Users\\Administrator\\Desktop\\New_microtable\\HUMAnN") # 根据实际路径修改
pathways_df <- read.table("kegg_abundance.txt", header = TRUE, stringsAsFactors = FALSE)# 初始化结果数据框
pathways_df$pathway_name <- NA
pathways_df$pathway_description <- NA
pathways_df$pathway_class <- NA
pathways_df$pathway_map <- NA#获取每个Pathway的详细信息
for (i in 1:nrow(pathways_df)) {pathway_id <- pathways_df$Pathway[i]# 获取Pathway信息pathway_info <- tryCatch(keggGet(pathway_id)[[1]], error = function(e) NULL)# 如果获取到信息，则提取并添加到结果数据框中if (!is.null(pathway_info)) {pathways_df$pathway_name[i] <- ifelse(!is.null(pathway_info$NAME), pathway_info$NAME, NA)pathways_df$pathway_description[i] <- ifelse(!is.null(pathway_info$DESCRIPTION), pathway_info$DESCRIPTION, NA)pathways_df$pathway_class[i] <- ifelse(!is.null(pathway_info$CLASS), pathway_info$CLASS, NA)pathways_df$pathway_map[i] <- paste0("http://www.kegg.jp/kegg-bin/show_pathway?", pathway_id)}
}# 保存结果到新的文本文件
write.table(pathways_df, file = "pathways_with_details.txt", quote = FALSE, row.names = FALSE, sep = "\t")
