I'm currently analysing a microarray dataset, on which I'm trying to detect the difference of gene expression between responders and non responders to a treatment.
Even after reading the Limma user guide and searching on the forum I'm not really sure which design matrix I should use for the comparison.
Here is a simplified model of my dataset :
cy3 cy5 responder RNA_reference RNA_reference responder non_responder RNA_reference RNA_reference non_responder moderate_responder RNA_reference RNA_reference moderate_responder
For example, I would like to detect differentialy expressed genes between responders and non responders, without taking moderate responders arrays into account. I think I understand it corresponds to a "separate channel analysis" like in the example of the chapter 12 of the Limma guide, but it slighty differs because here I use the same reference in all arrays, so I'm a bit lost on what I should do.
If anyone have an idea on what good design would be good for this analysis it would be very helpful.