
Hi Gordon and LIMMA users,
 
I am sure this question has been answered before and I tried looking into the archives for some answer but did n't have any success there.
 
My experimental design has diseased and healthy volunteers blood treated with a drug. I have gene expression data for both before and after treatment. So, I have disease, treatment and patient_ID (before vs. after treatment) as covariates. What I am interested in are as follows:
 
1. What genes change in untreated disease vs. untreated healthy volunteers?
2. What genes change in treated disease vs. untreated disease blood samples?
3. What genes change in treated healthy volunteers vs. untreated healthy volunteers blood samples?
 
Design of the experiment:
design <- model.matrix(~ dis + tx + patient)
 
Based on the above design I am able to answer question 1. I was wondering how I would answer question 2 and 3 in a paired T -test (to account for before  vs. after treatment). Do I need to do some contrasts because I have been trying to work off the lmfit.
 
Any help would be greatly apreciated.
 
Thanks,
Som.
 
 
 

  		 	   		  
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