[BioC] Methods in decideTests (limma)

[Michal Kolář]

Dear Gordon,

many thanks for your help :)

Best regards,
Michal

On 6 Jun 2009, at 02:23, Gordon K Smyth wrote:

> 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