[BioC] Methods in decideTests (limma)

[Gordon K Smyth]

Dear Michal,

On Fri, 5 Jun 2009, Michal Kolar wrote:

> Dear Gordon,
>
> thank you for your answer. I read the Section 10.3, yet I wanted to get 
> little more details. I should have searched in the List, as now I have been 
> able to find answers to many of my questions in previous posts (by you and 
> James W. MacDonald). I, however, still have one question.

...

> I have a 2*2 factorial design with surgery and treatment factors and their 
> interaction
>
>> design <- model.matrix(~surgery*treatment).
>
> The interaction term is potentially of interest. Do I gauge the 
> importance of the interaction term using decideTests with the method 
> "global" or "separate"? Or should I estimate the importance directly by 
> observing the distribution of p-values for the interaction term? If so, 
> should I remove all contrasts with, say, flat distribution of p-values 
> from the decideTests("global") call?

I cannot tell you how analyse a specific data set.  However statistical 
answers should always be tuned to the question at hand.  Your question, as 
you state it, concerns only the interaction, so it is naturally answered 
by a separate test of the interaction contrast.  A "global" call is always 
an answer to a question involving more than one contrast, and you have not 
asked such a question.  What I am saying is that you have to think 
carefully about all the scientific questions you really want to answer, 
then your formulation of the questions drives the analysis.

Best wishes
Gordon