Hi,all,
I used edgeR and DESeq to do RNAseq analysis. EdgeR gave me 236 genes, while DESeq gave me 49 genes. And the 49 genes in DESeq are all belong to the 236 genes of EdgeR. I wonder is this normal phenomenon?
And I don,t know whether it is because the different filtering process. In edgeR , I use the filtering in the following:
> keep<-rowSums(cpm(y)>1)>=3
> y<-y[keep,]
while in DESeq, I used the following filtering:
> rs=rowSums(counts(cds))
> theta=0.3
> use=(rs>quantile(rs,probs=theta))
> table(use)
> cdsFit=cds[use,]
Could anyone give me some suggestions? Thank you!
Best,
Sadiexiaoyu
I used edgeR and DESeq to do RNAseq analysis. EdgeR gave me 236 genes, while DESeq gave me 49 genes. And the 49 genes in DESeq are all belong to the 236 genes of EdgeR. I wonder is this normal phenomenon?
And I don,t know whether it is because the different filtering process. In edgeR , I use the filtering in the following:
> keep<-rowSums(cpm(y)>1)>=3
> y<-y[keep,]
while in DESeq, I used the following filtering:
> rs=rowSums(counts(cds))
> theta=0.3
> use=(rs>quantile(rs,probs=theta))
> table(use)
> cdsFit=cds[use,]
Could anyone give me some suggestions? Thank you!
Best,
Sadiexiaoyu
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