There are 104 samples, 38 samples are treated, 66 samples are control. The following script was used to do DGE analysis. But there is no any different expression genes, even though using the argument of dds$padj<0.05, alpha = 0.05, lfcThreshold=1. But there are more than 6000 DGEs, if you use edgeR, DEGSeq or GFOLD et al.
Would you like to tell me where is wrong? Or which soft package is more fit to do this analysis (with different replicates)? Thanks very much!
##==========================DESeq2--At-IW.LFC2.FDR001=======================
####for i in *.txt;do echo $i | awk '{printf ""%s",", substr($1,1,3)}';done
library('DESeq2')
directory <-"./At_Count/"
sampleFiles <- grep("*.txt",list.files(directory),value=TRUE)
sampleFiles
sampleCondition <- c("A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W")
sampleTable<-data.frame(sampleName=sampleFiles, fileName=sampleFiles, condition=sampleCondition)
sampleTable
ddsHTSeq<-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design=~condition)
ddsHTSeq
colData(ddsHTSeq)$condition<-factor(colData(ddsHTSeq)$condition, levels=c("A.I","A.W"))
#ddsHTSeq <- ddsHTSeq[rowSums(counts(ddsHTSeq)) >520,]
ddsHTSeq
dds<-DESeq(ddsHTSeq)
summary(dds)
table(dds$padj<0.001)
res<-results(dds,alpha = 0.05, lfcThreshold=2)
summary(res)
table(res$padj<0.05)
write.csv(as.data.frame(res),file="./At.IW.deseq2.MAplot.LFC2.Alp05.csv")
png(file="./At.IW.deseq2.MAplot.LFC2.Alp05.png",width=10,height=7.5,units="in",res=600)
layout(matrix(c(1,2,3,4,5,6), 1, 1, byrow=TRUE))
plotMA(res,ylim=c(-10,10),main="Improved VS Wild of At")
dev.off()
Would you like to tell me where is wrong? Or which soft package is more fit to do this analysis (with different replicates)? Thanks very much!
##==========================DESeq2--At-IW.LFC2.FDR001=======================
####for i in *.txt;do echo $i | awk '{printf ""%s",", substr($1,1,3)}';done
library('DESeq2')
directory <-"./At_Count/"
sampleFiles <- grep("*.txt",list.files(directory),value=TRUE)
sampleFiles
sampleCondition <- c("A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.I","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W","A.W")
sampleTable<-data.frame(sampleName=sampleFiles, fileName=sampleFiles, condition=sampleCondition)
sampleTable
ddsHTSeq<-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design=~condition)
ddsHTSeq
colData(ddsHTSeq)$condition<-factor(colData(ddsHTSeq)$condition, levels=c("A.I","A.W"))
#ddsHTSeq <- ddsHTSeq[rowSums(counts(ddsHTSeq)) >520,]
ddsHTSeq
dds<-DESeq(ddsHTSeq)
summary(dds)
table(dds$padj<0.001)
res<-results(dds,alpha = 0.05, lfcThreshold=2)
summary(res)
table(res$padj<0.05)
write.csv(as.data.frame(res),file="./At.IW.deseq2.MAplot.LFC2.Alp05.csv")
png(file="./At.IW.deseq2.MAplot.LFC2.Alp05.png",width=10,height=7.5,units="in",res=600)
layout(matrix(c(1,2,3,4,5,6), 1, 1, byrow=TRUE))
plotMA(res,ylim=c(-10,10),main="Improved VS Wild of At")
dev.off()