多个单细胞亚群各自标记基因联合进行GO和KEGG - 《scRNA》

#多个单细胞亚群各自标记基因联合进行GO和KEGG注释
rm(list=ls())
options(stringsAsFactors = F)
library(Seurat)
library(gplots)
library(ggplot2)
library(clusterProfiler)
pro='all'
#加载差异基因
load('sce.markers.all_10_celltype.Rdata')
table(sce.markers$cluster) #每个单细胞亚群都有自己的marker基因
library(org.Hs.eg.db)
ids=bitr(sce.markers$gene,
         'SYMBOL',
         'ENTREZID',
         'org.Hs.eg.db')
sce.markers=merge(sce.markers,
                  ids,
                  by.x='gene',
                  by.y='SYMBOL')
gcSample=split(sce.markers$ENTREZID, 
               sce.markers$cluster)
gcSample #entrez id , compareCluster

##KEGG
xx <- compareCluster(gcSample, 
                       fun="enrichKEGG",
                       organism="hsa", 
                       pvalueCutoff=0.05)
dotplot(xx)
ggsave(paste0(pro,'_kegg.pdf'))

图 KEGG

##BP 
  formula_res <- compareCluster(
    gcSample, 
    fun="enrichGO", 
    OrgDb="org.Hs.eg.db",
    ont = "BP",
    pAdjustMethod = "BH",
    pvalueCutoff  = 0.01,
    qvalueCutoff  = 0.05)

  #Run GO enrichment test and merge terms 
  # that are close to each other to remove result redundancy
  lineage1_ego <- simplify(
    formula_res, 
    cutoff=0.5, 
    by="p.adjust", 
    select_fun=min) 

  pdf(paste0(pro,'_GO_BP_cluster_simplified.pdf'),
      width = 15,
      height = 6)

  print(dotplot(lineage1_ego, 
                showCategory=5))
  dev.off() 
  write.csv(lineage1_ego@compareClusterResult, 
            file=paste0(pro,'_GO_BP_cluster_simplified.csv'))

图 BP

  ##CC 
  formula_res <- compareCluster(
    gcSample, 
    fun="enrichGO", 
    OrgDb="org.Hs.eg.db",
    ont    = "CC",
    pAdjustMethod = "BH",
    pvalueCutoff  = 0.01,
    qvalueCutoff  = 0.05)

  # Run GO enrichment test and merge terms 
  # that are close to each other to remove result redundancy
  lineage1_ego <- simplify(
    formula_res, 
    cutoff=0.5, 
    by="p.adjust", 
    select_fun=min) 
  pdf(paste0(pro,'_GO_CC_cluster_simplified.pdf'),
      width = 15,
      height = 6)
  print(dotplot(lineage1_ego,
                showCategory=5))
  dev.off() 
  write.csv(lineage1_ego@compareClusterResult, 
            file=paste0(pro,'_GO_CC_cluster_simplified.csv'))

图 CC

  ##MF 
  formula_res <- compareCluster(
    gcSample, 
    fun="enrichGO", 
    OrgDb="org.Hs.eg.db",
    ont    = "MF",
    pAdjustMethod = "BH",
    pvalueCutoff  = 0.01,
    qvalueCutoff  = 0.05)

  # Run GO enrichment test and merge terms 
  # that are close to each other to remove result redundancy
  lineage1_ego <- simplify(
    formula_res, 
    cutoff=0.5, 
    by="p.adjust", 
    select_fun=min
  ) 
  pdf(paste0(pro,'_GO_MF_cluster_simplified.pdf'),
      width = 15,
      height = 6)
  print(dotplot(lineage1_ego, 
                showCategory=5))
  dev.off() 
  write.csv(lineage1_ego@compareClusterResult, 
            file=paste0(pro,'_GO_MF_cluster_simplified.csv'))

图 MF