[BioC] Limma: how to obtain P values using method "global" for multiple testing

[Ribeiro,Eduardo de Souza]

Thank you very much Dr. Smyth. It worked fine for my model.

Eduardo de Souza Ribeiro
PhD student
University of Florida
________________________________________
From: Gordon K Smyth [smyth at wehi.EDU.AU]
Sent: Saturday, July 21, 2012 8:21 PM
To: Ribeiro,Eduardo de Souza
Cc: Bioconductor mailing list
Subject: Limma: how to obtain P values using method "global" for multiple testing

If fit is the fitted model object that you used for decidedTests(), then

   Global.Adjusted.P <- fit$p.value
   Global.Adjusted.P[] <- p.adjust(Global.Adjusted.P, method="BH")

Gordon


> Date: Sat, 21 Jul 2012 02:02:46 +0000
> From: "Ribeiro,Eduardo de Souza" <ribeiro.es at ufl.edu>
> To: "bioconductor at r-project.org" <bioconductor at r-project.org>
> Subject: [BioC] Limma: how to obtain P values using method "global"
>       for multiple testing
>
> Hi everyone,
>
> I am analyzing a Affymetrix microarray data set using the Limma package.
> According to my experimental design, I understand that my contrasts are
> closely related and that I should use the "global" method for multiple
> testing. My question is: Is there a way to obtain P-values using the
> "global" method for multiple testing? The decideTest function allows to
> specify the method "global" but just give the matrix of the results and
> not the P-values. And if I understood correctly, the topTable function
> does not allow to specify the method for multiple testing and uses the
> "separate" method as default. Comparing the decideTest matrices, I
> realize that the results of "separate" and "global" methods are slightly
> different and I am concerned that this difference may change the final
> interpretation of my study.
>
> Thank you very much.
>
> Best regards
>
> Eduardo Ribeiro
> PhD student
> University of Florida

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