GO and KEGG

2021-10-10

rm(list = ls())
setwd("D:/R/R-4.0.5/bin/project_writing/LIM/GO")

#BiocManager::install("clusterProfiler")
library(clusterProfiler)

## 

## clusterProfiler v4.0.5  For help: https://yulab-smu.top/biomedical-knowledge-mining-book/
## 
## If you use clusterProfiler in published research, please cite:
## T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation. 2021, 2(3):100141. doi: 10.1016/j.xinn.2021.100141

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## 载入程辑包：'clusterProfiler'

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library(ggplot2)
library(enrichplot)
library(GOplot)

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library(stringr)

#只要输入基因列表即可
glist <-read.table("glist62.txt",header = F)
glist <- glist$V1
#转化为'ENTREZID'
gene <- bitr(glist,fromType = 'SYMBOL',toType = 'ENTREZID',OrgDb = 'org.Hs.eg.db')

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## 'select()' returned 1:1 mapping between keys and columns

#GO富集
GO <- enrichGO(
  gene$ENTREZID,
  OrgDb = 'org.Hs.eg.db',
  keyType = "ENTREZID",
  ont = "ALL",
  pvalueCutoff = 0.05,
  pAdjustMethod = "BH",
  qvalueCutoff = 0.05,
  minGSSize = 10,
  maxGSSize = 500,
  readable = TRUE
) 

#KEGG富集
KEGG <- enrichKEGG(
  gene$ENTREZID,
  organism = "hsa",#用到是数据是人的组织数据
  keyType = "kegg",
  pvalueCutoff = 0.05,
  pAdjustMethod = "BH",
  minGSSize = 5,
  maxGSSize = 500,
  qvalueCutoff = 0.2,
  use_internal_data = FALSE) 

## Reading KEGG annotation online:

## Reading KEGG annotation online:

#绘图
#GO聚类条形图
barplot(GO, split="ONTOLOGY")+
  facet_grid(ONTOLOGY~., scales = "free") 

#GO聚类气泡图
dotplot(GO, split="ONTOLOGY")+
  facet_grid(ONTOLOGY~., scales ="free") 

#KEGG聚类条形图
barplot(KEGG,showCategory = 40,title = 'KEGG Pathway') 

#网络图
#GO通路-基因网络图
enrichplot::cnetplot(GO,circular=TRUE,colorEdge = TRUE)

#KEGG通路-基因网络图
enrichplot::cnetplot(KEGG,circular=TRUE,colorEdge = TRUE)