#if (!requireNamespace("BiocManager", quietly = TRUE))
#    install.packages("BiocManager")
#BiocManager::install("limma")
#BiocManager::install("org.Hs.eg.db")
#BiocManager::install("DOSE")
#BiocManager::install("clusterProfiler")
#BiocManager::install("enrichplot")


#引用包
library(limma)
library(org.Hs.eg.db)
library(clusterProfiler)
library(enrichplot)

gene="CLEC1B"                #基因名称
expFile="TCGA.TPM.txt"     #表达数据文件
gmtFile="c2.cp.kegg.v7.4.symbols.gmt"     #基因集文件
setwd("C:\\biowolf\\immWGCNA\\37.GSEA")      #设置工作目录

#读取文件,并对输入文件进行整理
rt=read.table(expFile, header=T, sep="\t", check.names=F)
rt=as.matrix(rt)
rownames(rt)=rt[,1]
exp=rt[,2:ncol(rt)]
dimnames=list(rownames(exp),colnames(exp))
data=matrix(as.numeric(as.matrix(exp)),nrow=nrow(exp),dimnames=dimnames)
data=avereps(data)
data=data[rowMeans(data)>0,]

#删掉正常样品
group=sapply(strsplit(colnames(data),"\\-"), "[", 4)
group=sapply(strsplit(group,""), "[", 1)
group=gsub("2", "1", group)
data=data[,group==0]
data=t(data)
rownames(data)=gsub("(.*?)\\-(.*?)\\-(.*?)\\-.*", "\\1\\-\\2\\-\\3", rownames(data))
data=t(avereps(data))

#根据目标基因表达量对样品进行分组，得到高低表达组的logFC
dataL=data[,data[gene,]<median(data[gene,]),drop=F]
dataH=data[,data[gene,]>=median(data[gene,]),drop=F]
meanL=rowMeans(dataL)
meanH=rowMeans(dataH)
meanL[meanL<0.00001]=0.00001
meanH[meanH<0.00001]=0.00001
logFC=log2(meanH)-log2(meanL)
logFC=sort(logFC,decreasing=T)
genes=names(logFC)

#读取基因集文件
gmt=read.gmt(gmtFile)

#富集分析
kk=GSEA(logFC, TERM2GENE=gmt, pvalueCutoff = 1)
kkTab=as.data.frame(kk)
kkTab=kkTab[kkTab$pvalue<0.05,]
#kkTab=kkTab[kkTab$p.adjust<0.05,]
write.table(kkTab,file="GSEA.result.txt",sep="\t",quote=F,row.names = F)
	
#绘制GSEA富集的图形
termNum=8     #展示通路的数目
if(nrow(kkTab)>=termNum){
	showTerm=row.names(kkTab)[1:termNum]
	gseaplot=gseaplot2(kk, showTerm, base_size=8, title=gene)
	pdf(file="GSEA.pdf", width=7.5, height=5.5)
	print(gseaplot)
	dev.off()
}