[BioC] finding and averaging replicate gene records

[Tomas Radivoyevitch]

Agreed, my statements are strictly for Affy data.

As a separate remark, one thing I liked about using the maximum average, 
rather than say a P value to pick out the probe set to focus on, is that the 
rule can be applied across different designs without concerns of statistical 
assumptions and choices of tests. For example, I also used maximum averages 
to pick out "useful" probe sets for one group time course data.
Tom


----- Original Message ----- 
From: "Sean Davis" <sdavis2 at mail.nih.gov>
To: "Tomas Radivoyevitch" <radivot at hal.epbi.cwru.edu>
Cc: <bioconductor at stat.math.ethz.ch>
Sent: Wednesday, March 16, 2005 8:48 AM
Subject: Re: [BioC] finding and averaging replicate gene records


>
> On Mar 16, 2005, at 8:31 AM, Tomas Radivoyevitch wrote:
>
>> Agreeing with Sean here, in my last experience where I had to reduce each 
>> gene to a single metric, using Affy data I found that taking the probe 
>> set with the maximum average value across all chips in the dataset worked 
>> well [e.g. in two group situations the resulting choices tended to be 
>> probe sets with smaller (if not the smallest) P values].
>
> This may work well with Affy, where lower values are perhaps less "stable" 
> than higher values, but I'm not sure it would work in every situation. 
> For example, on other platforms, the maximum average spot may signify 
> scanner saturation.  Moving to ratios, choosing the genes with the highest 
> (or lowest) ratio may signify lack of expression (or saturation for lowest 
> ratio) in the reference sample; in neither case would these genes be 
> "believable" and perhaps another probe for the same gene might point that 
> out.
>
> Seeing Tomas's point, if one does go ahead and summarize probes into 
> genes, caution must be exercised to choose the appropriate summary measure 
> and note should be made that such summaries might produce bias in the 
> genes found (and more importantly, validated, or not).
>
> Sean
>
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