#文件需要:所有基因的logFC数据all.txt,所有基因的表达量数据allExp.csv,所有差异显著基因的logFC,diff_AllGene.txt,免疫基因的名字
#第一个小目标:提取差异表达的免疫基因的logFC数据及表达量数据
setwd("C:/Users/仙女/Documents/liver cancer")
rt=read.table("all.txt",sep="\t",header = T,check.names = F,row.names = 1)
allExp=read.csv("allExp.csv")
row.names(allExp)=allExp[,1]
allExp=allExp[,-1]
diffExp=read.table("diff_AllGene.txt",sep="\t",header = T,check.names = F,row.names = 1)
gene=read.table("immune_gene.txt",sep="\t",header = F)
immuneDiffALL=rt[intersect(gene[,1],row.names(rt)),]
#提取免疫基因相关的所有差异表达数据
immuneDiffGene=intersect(gene[,1],row.names(diffExp))
#从差异表达的基因中提取与免疫有关的基因,这里只提取了基因这一列
#用intersect函数将gene的第一列与diffExp的行名取交集
hmExp=allExp[immuneDiffGene,]
immuneDiffResult=immuneDiffALL[immuneDiffGene,]
#将差异免疫基因从免疫相关所有差异表达数据中提取出来
#输出免疫基因的差异结果
immuneDiffResult=rbind(ID=colnames(immuneDiffResult),immuneDiffResult)
write.csv(immuneDiffResult,file="immune_Diff.csv")
#输出差异免疫基因的表达量
immuneGeneExp=rbind(ID=colnames(hmExp),hmExp)
write.csv(immuneGeneExp,file="immuneGeneExp.csv")
write.csv(immuneGeneExp,file="TFGeneExp.csv")
第二个小目标:绘制火山图
library(pheatmap)
#绘制火山图
#横坐标是logFC,纵坐标是-log10(fdr)fdr是调整过得Pvalue,也可以是pvalue
pdf(file="vol.pdf",height = 5,width=5)
xMax=max(abs(as.numeric(as.vector(immuneDiffALL$logFC))))
yMax=max(-log10(immuneDiffALL$fdr))+1
a=as.numeric(as.vector(immuneDiffALL$logFC))
b=-log10(immuneDiffALL$fdr)
plot(a,b,xlab = "logFC",ylab = "-log10(fdr)",
main="Volcano",ylim=c(0,yMax),xlim=c(-xMax,xMax),yaxs="i",pch=20,cex=0.8)
diffSub=subset(immuneDiffALL,fdr
points(as.numeric(as.vector(diffSub$logFC)),-log10(diffSub$fdr),pch=20,col="red",cex=0.8)
diffSub=subset(immuneDiffALL,fdr points(as.numeric(as.vector(diffSub$logFC)),-log10(diffSub$fdr),pch=20,col="green",cex=0.8) abline(v=0,lty=2,lwd=3) dev.off() 第三个小目标:绘制热图 #绘制差异基因热图 hmExp=log2(hmExp+0.001) #这个0.001是随便加的,hmExp是差异免疫基因的logFC等数据 Type=c(rep("N",conNum),rep("C",treaNum)) names(Type)=colnames(hmExp) Type=as.data.frame(Type) pdf(file="heatmap.pdf",height = 12,width = 15) pheatmap(hmExp, annotation = Type,#分组 color = colorRampPalette(c("green","black","red"))(50), cluster_cols = F, show_colnames = F, show_rownames = F, fontsize = 12, fontsize_row = 3, fontsize_col = 10) dev.off()