**80**wrote:

I am conducting differential expression analysis in limma for a time course microarray experiment. I have 3 time points (1,2,3) and two conditions (control,disease). My contrast is formulated as:

```
pheno<-factor(c("disease.1","disease.1","disease.2","disease.2","disease.3","disease.3","control.1","control.1","control.2","control.2","control.3","control.3")
model<-model.matrix(~0+pheno)
```

contrast<-makeContrasts(disease.1-control.1, disease.2-control.2, disease.3-control.3,levels=model) fit<-lmFit(expression,model) fit2<-contrasts.fit(fit,contrast) fit2<-eBayes(fit2) topTableF(fit2)

How can I apply SVA with this experimental setup? Or is there an alternative? The challenge I am facing is SVA seems designed for two class experiments, because the null model requires leaving out the variable of interest, however in this case there isn't one variable but many.

Thanks!

**6.0k**• written 5.5 years ago by tucanj •

**80**