library(clusterProfiler)
library(org.Hs.eg.db)
# 读取输入数据文件
file_path <- "C:/Users/Lamarck/Desktop/UP_genes_ENSEMBL_ENTREZID.csv"
data <- read.csv(file_path, header = TRUE)
# 提取基因列表（ENTREZID）
gene <- data$ENTREZID
# KEGG 富集分析
kegg_result <- enrichKEGG(
gene = gene,
organism = "hsa",
pvalueCutoff = 1,
qvalueCutoff = 1
)
# 结果转为数据框
kegg_frame <- as.data.frame(kegg_result)
rownames(kegg_frame) <- 1:nrow(kegg_frame)
# 添加排序变量（用于后续可视化）
kegg_frame$order <- factor(rev(seq_len(nrow(kegg_frame))), labels = rev(kegg_frame$Description))
# 保存结果
output_path <- "C:/Users/Lamarck/Desktop/kegg_frame.csv"
write.csv(kegg_frame, file = output_path, row.names = FALSE)本站原创，如若转载，请注明出处：https://www.ouq.net/3772.html
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