seurat如何批量对cluster marker做富集

最新推荐文章于 2024-06-12 20:43:17 发布

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这段代码使用R语言的clusterProfiler包进行批量分析，针对15个不同的细胞簇（cluster）找到标记基因，并进行GO富集和KEGG通路富集分析。每个集群的富集结果分别保存为CSV文件，同时保存了标记基因的详细信息。这有助于理解不同细胞状态的功能特性。

如何批量的对每个cluster findmarker并富集

library(clusterProfiler)
library(ggplot2)
for(j in 0:15) {
  cluster.markers <- FindMarkers(object = sce_endo, ident.1 = j, logfc.threshold = 0.25, test.use = "bimod", only.pos = TRUE)
  cluster <- row.names.data.frame(cluster.markers)
  cluster = bitr(cluster,fromType = "SYMBOL",toType = c("ENTREZID"),OrgDb = "org.Hs.eg.db")
  cluster.go <- enrichGO(gene = cluster[,"ENTREZID"], keyType = "ENTREZID",OrgDb = 'org.Hs.eg.db',ont = "ALL",pAdjustMethod = "BH",pvalueCutoff = 0.01,qvalueCutoff = 0.05,readable = TRUE)
  assign(paste0("cluster",j,".go"),cluster.go)
  write.csv(cluster.go@result, file = paste0("cluster",j,"go",".csv"))
  
  cluster.kegg <- enrichKEGG(gene = cluster[,"ENTREZID"],organism = 'hsa', pvalueCutoff = 0.05,pAdjustMethod = 'BH', minGSSize = 10,maxGSSize = 500,qvalueCutoff = 0.2,use_internal_data = FALSE)
  assign(paste0("cluster",j,".kegg"),cluster.kegg)
  write.csv(cluster.kegg@result, file = paste0("cluster",j,"kegg",".csv"))
  write.csv(x = cluster.markers,file = paste0("cluster",j,".csv"))
}