[BioC] Handling "nested" factors in limma

Gordon Smyth smyth at wehi.edu.au
Thu Dec 9 00:25:18 CET 2004

>Date: Mon, 6 Dec 2004 13:41:35 -0000
>From: "michael watson \(IAH-C\)" <michael.watson at bbsrc.ac.uk>
>Subject: [BioC] Handling "nested" factors in limma
>To: <bioconductor at stat.math.ethz.ch>
>Consider the design matrix in the limma user guide, section 10.7:
>FileName        Strain  Treatment
>File1   WT      U
>File2   WT      S
>File3   Mu      U
>File4   Mu      S
>File5   Mu      S
>Does it matter if these samples are from five different mice, or only
>two (WT and Mu) where different treatments have been applied to the same
>mouse at different times?

Yes, it makes a fundamental difference to the conclusions you can make from 
the experiment. The difference is to do with science rather than with limma 
or with statistical computations. It means that any conclusions you make 
from the experiment would apply only to these two mice, not to wildtype and 
mutant mice in general, because you have not estimated the variability of 
mice within the two populations.

Observing both U and S on each mouse would be a good idea if you had more 
than one mouse per strain. However the model would then be more complicated 
-- you would have 3-factors, or rather 2-factors with a blocking structure.

>Does this nesting change how we apply the
>design and contrasts matrices in limma?



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