[BioC] test for differential expresssion

Gordon K Smyth smyth at wehi.EDU.AU
Fri Jun 28 01:52:38 CEST 2013

Dear Xiayu,

> Date: Wed, 26 Jun 2013 17:47:22 +0000
> From: "Rao,Xiayu" <XRao at mdanderson.org>
> To: "'bioconductor at r-project.org'" <bioconductor at r-project.org>
> Subject: [BioC] test for differential expresssion
> Hello,
> Thank you in advance for your help!
> I have 16 tumor samples and each one has a corresponding normal sample, 
> which are 16 pairs. For one particular pair, there is a matched 
> metastasis sample. When I analyzed the data using limma package and 
> followed their protocol, is it right that I fit a linear model, and 
> compare two contrasts of Tumor vs. Normal, and Metastasis vs. Normal?

This is fine.

Of course the genewise variability has to estimated purely from the tumor 
samples; the metastisized sample doesn't contribute to the variability 
estimate because there is only one.  Also the statistical test of 
metastasis vs normal will not be very powerful, because it is based on 
only one sample.  Nevertheless, it can all be done.

> Or should I ignore that 1 metastasis sample and just use paired ttest to 
> test between Tumor and Normal?

It makes no difference.  The limma paired t-test of tumor vs normal will 
be exactly the same whether or not the metastasis sample is included. 
The metastasis sample doesn't contribute to the genewise variability 
estimate, so it makes no difference to the test of tumor vs normal whether 
or not it is incuded in the data.

You may as well include all the data.  That is the philosophy behind the 
limma package.

Best wishes

> Best,
> Xiayu

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