Hi Jose,
   
  Let's say we have 4 treatments, 3 replicates each. I am interested in comparing 1vs2, 1vs3 and 1vs4. I assume that instead of making pairwise comparisons it would be better to use something like the following script.
   
  temp<-normalizeBetweenArrays(log2(signals), method='quantile')
design <- model.matrix(~0 +factor(c(1,1,1,2,2,2,3,3,3,4,4,4)))
colnames(design) <- c("T1","T2","T3","T4")
contrast.matrix <-
 makeContrasts(T2-T1, T3-T1, T4-T1, levels=design)
fit <- lmFit(temp, design)
fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2)
   
  So, all treatments are included in lmFit to get more power. Let's suppose a probe has "negligible" signal in 1, 2 and 3, but very strong signal in 4. It would mean that for this probe T2-T1 and T3-T1 could produce erroneous results and also would negatively influence T4-T1 as lmFit would estimate parameters gathering information across all 4 treatments.
   
  Is it reasonable?
  Thank you,
  Lev.

   
   
   
  J.delasHeras@ed.ac.uk wrote:
  Quoting Lev Soinov :

> Hi Jose,
>
> Yes, I totally understand the point about losing some probes that 
> are "not expressed" in one treatment but "expressed" in some other 
> treatments. However, let's say we have 4 treatments, comparing 1vs2, 
> 1vs3 and 1vs4 in LIMMA. If I am not mistaken, it is recommended to 
> process all treatments together to get more power. Suppose a probe 
> has "negligible" signal in 1, 2 and 3, but very strong signal in 4. 
> You would obviously keep it, according to you procedure, and you 
> would be absolutely right if you were interested in 1vs4 only. 
> However, in this particular situation 1vs2 and 1vs3 doesn't make 
> much sense and could produce false positive results. Also, if 1, 2 
> and 3 do not contain "true" signals but only some near-background 
> noise, how would it help to estimate the variance for this probe? I 
> may be wrong here, but it seems to me that information from 1, 2 and 
> 3 would just add more error in lmFit, thus obscuring inferences for 
> 1vs4 as well.
>
> Thank you,
> Lev.

Hi Lev,

I must admit I don't quite follow the way you pick comparisons and probes.
If I want to analyse comparisons between all 4 treatments, and a probe 
is only present in one of them, say number 4, I'd probably keep it. If 
you want to remove it because it's only expressed in one of them, 
that's your call, but I'd keep it: I am looking for differences 
between treatments, and right there there's a clear one between 4 and 
all teh others... why lose it? Just to improve the FDR a little? I 
don't understand that rationale.
It's not how I would go about things, but it probably depends on the 
actual experiment and what your goal is. If I don't care about things 
that are different between treatment 4 and the other three... then I'd 
just leave treatment 4 out altogether.

I'm sorry if I am not fully understanding you.

Jose

-- 
Dr. Jose I. de las Heras Email: J.delasHeras@ed.ac.uk
The Wellcome Trust Centre for Cell Biology Phone: +44 (0)131 6513374
Institute for Cell & Molecular Biology Fax: +44 (0)131 6507360
Swann Building, Mayfield Road
University of Edinburgh
Edinburgh EH9 3JR
UK



 		
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