下载了TCGA的Rna-seq数据后分别用了DECenter和r中的edgeR包进行分析，完全按照教程来操作的，但得出结果有很大不同，求各位大神解答！还有按提示方法用DESeq2包进行分析时出现错误，求解！

edgeR代码如下：

#edgeR

source("http://bioconductor.org/biocLite.R")   

biocLite("edgeR")

install.packages("gplots")

foldChange=2

padj=0.01

setwd("F:\\2database\\colorectal\\mrna")                    #设置工作目录

library("edgeR")

rt=read.table("mrna.txt",sep="\t",header=T,check.names=F)  #改成自己的文件名

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)>1,]

group=c(rep("normal",375),rep("tumor",18))                         #按照癌症和正常样品数目修改

design <- model.matrix(~group)

y <- DGEList(counts=data,group=group)

y <- calcNormFactors(y)

y <- estimateCommonDisp(y)

y <- estimateTagwiseDisp(y)

et <- exactTest(y,pair = c("normal","tumor"))

topTags(et)

ordered_tags <- topTags(et, n=100000)

allDiff=ordered_tags$table

allDiff=allDiff[is.na(allDiff$FDR)==FALSE,]

diff=allDiff

newData=y$pseudo.counts

write.table(diff,file="edgerOut.xls",sep="\t",quote=F)

diffSig = diff[(diff$FDR < padj & (diff$logFC>foldChange | diff$logFC<(-foldChange))),]

write.table(diffSig, file="diffSig.xls",sep="\t",quote=F)

diffUp = diff[(diff$FDR < padj & (diff$logFC>foldChange)),]

write.table(diffUp, file="up.xls",sep="\t",quote=F)

diffDown = diff[(diff$FDR < padj & (diff$logFC<(-foldChange))),]

write.table(diffDown, file="down.xls",sep="\t",quote=F)

normalizeExp=rbind(id=colnames(newData),newData)

write.table(normalizeExp,file="normalizeExp.txt",sep="\t",quote=F,col.names=F)   #输出所有基因校正后的表达值（normalizeExp.txt）

diffExp=rbind(id=colnames(newData),newData[rownames(diffSig),])

write.table(diffExp,file="diffmRNAExp.txt",sep="\t",quote=F,col.names=F)         #输出差异基因校正后的表达值（diffmRNAExp.txt）