logFoldChange=1
adjustP=0.05

library(limma)
library("impute")
setwd("D:\\徐周洋\\发表的论文成果\\SCI\\原始数据\\文章1\\差异基因")

rt=read.table("geneMatrix.txt",sep="\t",header=T)
rt=as.matrix(rt)
rownames(rt)=rt[,1]
exp=rt[,2:ncol(rt)]
dimnames=list(rownames(exp),colnames(exp))
exp=matrix(as.numeric(as.matrix(exp)),nrow=nrow(exp),dimnames=dimnames)
mat=impute.knn(exp)
rt=mat$data

rt=avereps(rt)

boxplot(rt,col = "red",xaxt = "n",outline = F)

rt=normalizeBetweenArrays(as.matrix(rt))

boxplot(rt,col = "red",xaxt = "n",outline = F)

rt=log2(rt)             

class <- c(rep("con",12),rep("treat",18)) 
design <- model.matrix(~0+factor(class))
colnames(design) <- c("con","treat")
fit <- lmFit(rt,design)
cont.matrix<-makeContrasts(treat-con,levels=design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2)

allDiff=topTable(fit2,adjust='fdr',number=200000)
write.table(allDiff,file="limmaTab.xls",sep="\t",quote=F)
allLimma=allDiff
allLimma=allLimma[order(allLimma$logFC),]
allLimma=rbind(Gene=colnames(allLimma),allLimma)
write.table(allLimma,file="limmaTab.txt",sep="\t",quote=F,col.names=F)


diffSig <- allDiff[with(allDiff, (abs(logFC)>logFoldChange & adj.P.Val < adjustP )), ]
write.table(diffSig,file="diff.xls",sep="\t",quote=F)
diffUp <- allDiff[with(allDiff, (logFC>logFoldChange & adj.P.Val < adjustP )), ]
write.table(diffUp,file="up.xls",sep="\t",quote=F)
diffDown <- allDiff[with(allDiff, (logFC<(-logFoldChange) & adj.P.Val < adjustP )), ]
write.table(diffDown,file="down.xls",sep="\t",quote=F)

hmExp=rt[rownames(diffSig),]
diffExp=rbind(id=colnames(hmExp),hmExp)
write.table(diffExp,file="diffExp.txt",sep="\t",quote=F,col.names=F)