Thank you for your reply Martin,

 

I have performed microarray with two of the same genotypes and tissues
before and they showed quite a bit of differential expression and two of the
other genotypes are similar to the two I used before. Two interesting
observations are that the p-values between some of the treatments come back
identical for every gene and also that the B-statistic (in limma) is a
negative value. As I don't have much experience with this, I don't know what
to make of it. Any help would be greatly appreciated.

 

Darren

 

  _____  

From: martin.schumacher@novartis.com [mailto:martin.schumacher@novartis.com]

Sent: Thursday, June 01, 2006 1:36 AM
To: Darren Ames
Subject: Re: [BioC] flat microarray p-values

 


Dear Darren, 

Under the null hypothesis (no differences between conditions) the p-values
are uniformly distrisbuted. This indicates that what you find is not
different from what you would expect by pure change. However, this does not
exclude that individual genes are differentially expressed. 

Best regards, 
Martin 







 

"Darren Ames" <ames@Ag.arizona.edu> 
Sent by: bioconductor-bounces@stat.math.ethz.ch 

01.06.2006 00:23 

        
        To:        <bioconductor@stat.math.ethz.ch> 
        cc:        (bcc: Martin Schumacher/PH/Novartis) 
        Subject:        [BioC] flat microarray p-values 

        Category:         




I have a problem with my latest batch of microarrays. A histogram of all the
p-values is flat, so the qvalue package does not work. Quality control
indicates that these are good arrays. Does anyone have any ideas?



Darren


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