I have been working on microarrays using R and Limma for differential gene expression analysis. My current design is fairly simple as I am just using two class "control" and "treatment"
design <- model.matrix(~cell_class, data)
But the data also contains different cell lines, so I have been wondering if it would be better to use another design like so:
design <- model.matrix(~cell_class + cell_lines, data)
Both designs lead to very similar output, almost all DE genes are the same but with slight differences in fold change and FDR. I have been searching in limma documentation and a few papers without a clear answer so far.