[BioC] No replicates and differential analysis !!

[Wolfgang Huber]

Hi Nicolas,

 > And it is
 > supported that the FC tends to be greater at low expression levels.

What is supported is that the variance of the _estimate_ of the FC (the 
true underlying quantity) by the log-ratio of measured probe intensities 
tends to be greater at low expression levels. Indeed this depends on the 
preprocessing and background correction. Consider this paper:

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12169536

and the accompanying "vsn" package in bioC. It removes the 
intensity-dependence of the variance, and you can use the "glog-ratio", 
which is an alternative estimator of FC, to select genes. This amounts 
to assuming that all genes have the same variance.

Of course the assumption is not really true, there can be gene-specific 
causes for different variances (besides overall intensity). But with 
only two arrays you have no way of seeing them. Hence, using glog-ratio 
to select genes when there are no replicates is an extreme version of 
the moderated t-statistic (which is often used when there are few 
replicates).

  Best wishes
  Wolfgang




Nicolas Servant wrote:
> Thanks for your answer,
> But in this case, i have to choose a fold change threshold ! And it is 
> supported that the FC tends to be greater at low expression levels.
> For instance a FC greater than 2 for expression values near 50 is 
> readily seen, but it is low probability to observe FC greater than 2 for 
> expression values near 1000
> So i would like to use a more robust approach.
> 
> Regards,
> Nicolas S.
> 
> Sean Davis wrote:
> 
> 
>>On 1/25/06 8:34 AM, "Nicolas Servant" <Nicolas.Servant at curie.fr> wrote:
>>
>> 
>>
>>
>>>Hello,
>>>
>>>Does anybody know a R package or function to compare expression level
>>>(affy data) of two groups with no replicates in each group ? In fact,
>>>just compare one array to an other.
>>>The purpose is to find differentially expressed genes.
>>>We cannot used statistical test (not enougth replicates), but we can
>>>used graphical approach based on scatter plot, and outliers detection
>>>approach.
>>>   
>>>
>>
>>Simply take array A and divide it by array B.  Then rank the genes by those
>>ratios.  
>>
>>Sean
>>
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>>
>>
>> 
>>
> 
> 
> 


-- 
Best regards
   Wolfgang

-------------------------------------
Wolfgang Huber
European Bioinformatics Institute
European Molecular Biology Laboratory
Cambridge CB10 1SD
England
Phone: +44 1223 494642
Fax:   +44 1223 494486
Http:  www.ebi.ac.uk/huber