Dear list,
I am not sure how to create the proper design in limma for my experiment which I think is a factorial and paired combined.

I have 9 patients that are on 3 different diets (3 patients each) and I have paired samples (pre and post) for each. So I have a total of 18 Affy arrays.

I want to mainly determine the genes that are affected in each diet. Then I also want to get the genes that are changing in the diets at the 'pre' stage to get an indication of the variation in my starting population. So I have made a targets file that looks like this:
targets
      ArrayNames Person    Diet Time
1  JALI-173_post    173 Control post
2   JALI-173_pre    173 Control  pre
3  JALI-205_post    205   lowFV post
4   JALI-205_pre    205   lowFV  pre
5  JALI-223_post    223 Control post
6   JALI-223_pre    223 Control  pre
7  JALI-225_post    225  highFV post
8   JALI-225_pre    225  highFV  pre
9  JALI-235_post    235   lowFV post
10  JALI-235_pre    235   lowFV  pre
11 JALI-245_post    245   lowFV post
12  JALI-245_pre    245   lowFV  pre
13 JALI-252_post    252  highFV post
14  JALI-252_pre    252  highFV  pre
15 JALI-263_post    263  highFV post
16  JALI-263_pre    263  highFV  pre
17 JALI-276_post    276 Control post
18  JALI-276_pre    276 Control  pre


then,

person<-factor(targets$Person)

diet<-factor(targets$Diet, levels=c("highFV","lowFV","Control"))

time<-factor(targets$Time, levels=c("Pre", "Post"))

So I am kind of stuck with the design and the model to use for my data and also how to make contrasts and get the comparisons I want.

Please can you give me any help?
Thanks in advance.
Maria



Maria Traka, PhD, MSc
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