Thanks for you prompt reply, James. I'm familiar with you from your postings on the SAM mailing lists, so am honoured that you can reply to my query.
Whilst I don't want to take bread out of honest statisticians mouths, I've been asked to analyse using limma an experiment that's already taken place - the design was down to someone else and obviously from your reply should have been done in a different way.
The experiment is quite simple in that spleen cells are incubated with or without a stimulant (I think it's the ppd of the TB vaccine) for either 4 or 8 hours, and the contrast of interest is whether there is a difference in gene expression in the stimulated cells between the two time periods.
I thought about analysing it using the "negs" as a common reference as you suggest, but that would assume that there is no change in expression in the unstimulated samples, which it not an assumption that now can be proved one way or the other.
Up until now, I had been analysing them seperately, and just comparing the lists of expressed genes, but thought that there could be more information obtained by trying to "link" them. If it could be done, then I could also answer the question of whether the unstimulated "negs" are in fact different at the two time points. 
I take it from your reply that this cannot actually be done now.

Thanks again for replying,
 
Jabez
--- On Fri, 22/5/09, James W. MacDonald <jmacdon@med.umich.edu> wrote:


From: James W. MacDonald <jmacdon@med.umich.edu>
Subject: Re: [BioC] Limma analyse factorial data with two-color arrays
To: "Jabez Wilson" <jabezwuk@yahoo.co.uk>
Cc: "bioconductor" <bioconductor@stat.math.ethz.ch>
Date: Friday, 22 May, 2009, 2:12 PM


Hi Jabez,

Jabez Wilson wrote:
> Sorry.... sent too soon.
> 
> Dear all, I know that this question has been asked in a couple of
> forms, but I haven't noticed a full reply given. I'm hoping that
> someone will be able to give me the exact answer. I'm comparing
> stimulated cells vs unstimulated cells on each slide at two time
> points (4 hrs and 8 hrs). Suppose there are 4 samples at each time
> point the targets file will look like this:
> 
> FileName cy3     cy5 1             stim4  neg4 2             neg4
> stim4 3             stim4  neg4 4             neg4   stim4
> 
> 5             stim8  neg8 6             neg8  stim8 7
> stim8  neg8 8             neg8   stim8
> 
> There is no common reference (pool) as there is in the weaver example
> in the limma guide, so should I use e.g. neg4 as the reference i.e.
> 
> design <- modelMatrix(targets,ref="neg4")
> 
> If I do that then when I fit the model using lmFit(MA, design) I get
> 
> "Coefficients not estimable: stim8 "

You can't use neg4 as a reference when it isn't actually a reference (e.g., it has to be on every slide). If you create a design matrix this way you will get

> modelMatrix(targets, ref="neg4")
Found unique target names:
neg4 neg8 stim4 stim8
     neg8 stim4 stim8
[1,]    0    -1     0
[2,]    0     1     0
[3,]    0    -1     0
[4,]    0     1     0
[5,]    1     0    -1
[6,]   -1     0     1
[7,]    1     0    -1
[8,]   -1     0     1

Which is not of full rank (e.g., the stim8 column is a linear combination of the neg8 column).

You don't give any information about your experiment, so it is difficult to help. In addition, people are in general hesitant to help people with experimental design or analysis questions because a.) that is what many of us do for a living, so you are in effect asking for pro bono work, and b.) without knowing more about a given experiment it isn't reasonable for people to give analysis advice anyway.

So, without knowing more about your experiment other than the short names you gave your treatments, can you not simply analyze the '4' samples separately from the '8' samples, using a reference design in each case? Or if the negX samples are all supposed to be similar in expression (and you can show they are), you could rename them 'neg' and then have a true reference design.

Best,

Jim


> 
> Can anyone help me from this point (apart from advising me to do the
> microarray expt with affymetrix chips)?
> 
> 
> 
> 
> 
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> 
> 
> 
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> 
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-- James W. MacDonald, M.S.
Biostatistician
Douglas Lab
University of Michigan
Department of Human Genetics
5912 Buhl
1241 E. Catherine St.
Ann Arbor MI 48109-5618
734-615-7826



      
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