Hi, friends, Is there someone could correct my default codes or thoughts? The highest appreciate from me. There are 6 samples with 2 kinds of treatments, like this:
array treatment GSM1 control-1 GSM2 control-2 GSM3 control-3 GSM4 Oxali-1 GSM5 Oxali-2 GSM6 Oxali-3
My aim is to compare the differential genes between "control" group and "Oxali" group, so I code like this:
> group=factor(rep(c("control","Oxali"),each=3),levels = c("Oxali","control")) > group2=relevel(group,"control") > design<-model.matrix(~factor(group2)) > rownames(design)=colnames(eSet) > fit =lmFit(eSet,design) > fit2=eBayes(fit) > result=topTable(fit2,coef = 2,n=Inf,adjust.method ="BH",sort.by="P") > sum(result$adj.P.Val<0.05)  1
The above codes look good, however, when I sum(result$adj.P.Val<0.05), there is only 1 result. That is so unreasonable, I must make some wrongs, while I don't find it. Another, the published article informs me that there are 267 up-regulation genes and 65 down-regulation genes, despite I set my cut-off values as p.value<0.05 & abs(logFC)>2, I get a wrong result different with article result.
My codes look good while working badly, I hope there are some kind friends can point out my drawback. Thank you very much!