[BioC] limma power question

Gordon Smyth smyth at wehi.edu.au
Sat Nov 6 04:35:11 CET 2004

>Date: Fri, 5 Nov 2004 03:31:08 +0100
>From: Anthony Bosco <anthonyb at ichr.uwa.edu.au>
>Subject: [BioC] limma power question
>To: bioconductor at stat.math.ethz.ch
>Message-ID: <f05111a06bdb094e4101c@[]>
>Content-Type: text/plain; charset="us-ascii" ; format="flowed"
>I am using limma to analyse an experiment where I am comparing the
>response in stimulated verses un-stimulated cells in individuals with
>and without disease.
>When I ask how individuals with or without disease respond
>differently to the stimulus there are no significant genes when the p
>values are adjusted.
>I know that there are differences which have been confirmed by
>qRT-PCR ( and can be demonstarted by analysing data using fold change
>only) and these genes have the highest ranked p values in the limma
>analysis (although not significant when adjusted).
>I have tried to filter the data set (to the 3000 most variable genes)
>so there are less comparisons being made and the differences are
>still not significant.
>I am using hgu133plus2 chips with 3 replicates.

What is your question?

As far as I know, the limma method has as good or better power than 
competing methods for this problem, but no guarantee is offered that 
significant results will always be provided.

If you already have a small group of genes that you have an apriori 
interest in, you can test for these genes only without adjusting the p-values.


>Anthony Bosco - PhD Student
>Institute for Child Health Research
>(Company Limited by Guarantee ACN 009 278 755)
>Subiaco, Western Australia, 6008
>Ph 61 8 9489  , Fax 61 8 9489 7700
>email anthonyb at ichr.uwa.edu.au

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