[BioC] GCRMA-induced correlations? LARGE Change in GCRMA expression values

[Richard Friedman]

Dear Zhijin,

	Has the change  that you described below been made in or before
GCRMA 2.12?

	If so has the new GCRMA been benchmarked at does it give
comparable results to the old GCRMA?

	I am noticing a large change in the absolute values of
intensity measurements

	For the same probeset and and array normalized with the same 8 other  
arrays done with
GCRMA 2.10 I got 5.27
but for
GCRMA 2.12  I got 3.14

Does this sound like a change that can be expected between versions
2.10 and 2.12

or does it sound as if I had made an error of some kind.

Thanks and best wishes,
Rich
------------------------------------------------------------
Richard A. Friedman, PhD
Associate Research Scientist,
Biomedical Informatics Shared Resource
Herbert Irving Comprehensive Cancer Center (HICCC)
Lecturer,
Department of Biomedical Informatics (DBMI)
Educational Coordinator,
Center for Computational Biology and Bioinformatics (C2B2)/
National Center for Multiscale Analysis of Genomic Networks (MAGNet)
Box 95, Room 130BB or P&S 1-420C
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(212)305-6901 (5-6901) (voice)
friedman at cancercenter.columbia.edu
http://cancercenter.columbia.edu/~friedman/

In Memoriam,
Arthur C. Clarke



On Feb 19, 2008, at 3:36 PM, Zhijin Wu wrote:

> Yes, to eliminate this artifact The truncated values will no longer be
> adjusted in the next release of GCRMA.
>
> Jenny Drnevich wrote:
>> Hi Zhijin,
>>
>> A client pointed out a July 2007 article by Lim et al. testing  
>> different
>> normalization/pre-processing methods for their effects on pairwise
>> correlations between probesets (Bioinformatics 2007 23(13):i282-i288;
>> doi:10.1093/bioinformatics/btm201; full link below). They reported  
>> that
>> GCRMA introduced severe artificial correlations between probesets;  
>> they
>> looked for a cause and think it's due truncation of low-intensity  
>> values
>> after Non-Specific Binding adjustment and then the Gene-Specific  
>> Binding
>> adjustment on these truncated values. They also tested a specific
>> correction to the GCRMA algorithm that appears to prevent the  
>> artificial
>> correlation and suggest that it become an option or even a default in
>> the R implementation of GCRMA.
>>
>> What do you think of this article? Are there any plans to implement
>> their suggestion?
>>
>> Thanks,
>> Jenny
>>
>> Comparative analysis of microarray normalization procedures:  
>> effects on
>> reverse engineering gene networks
>>
>> http://bioinformatics.oxfordjournals.org/cgi/content/full/23/13/ 
>> i282? 
>> maxtoshow=&HITS=10&hits=10&RESULTFORMAT=1&andorexacttitle=and&andorex 
>> acttitleabs=and&andorexactfulltext=and&searchid=1&FIRSTINDEX=0&sortsp 
>> ec=relevance&volume=23&firstpage=i282&resourcetype=HWCIT&eaf
>>
>>
>>
>> <http://bioinformatics.oxfordjournals.org/cgi/content/full/23/13/ 
>> i282? 
>> maxtoshow=&HITS=10&hits=10&RESULTFORMAT=1&andorexacttitle=and&andorex 
>> acttitleabs=and&andorexactfulltext=and&searchid=1&FIRSTINDEX=0&sortsp 
>> ec=relevance&volume=23&firstpage=i282&resourcetype=HWCIT&eaf>
>>
>> Jenny Drnevich, Ph.D.
>>
>> Functional Genomics Bioinformatics Specialist
>> W.M. Keck Center for Comparative and Functional Genomics
>> Roy J. Carver Biotechnology Center
>> University of Illinois, Urbana-Champaign
>>
>> 330 ERML
>> 1201 W. Gregory Dr.
>> Urbana, IL 61801
>> USA
>>
>> ph: 217-244-7355
>> fax: 217-265-5066
>> e-mail: drnevich at uiuc.edu
>>
>
>
> -- 
> -------------------------------------------
> Zhijin (Jean) Wu
> Assistant Professor of Biostatistics
> Brown University, Box G-S121
> Providence, RI  02912
>
> Tel: 401 863 1230
> Fax: 401 863 9182
> http://stat.brown.edu/~zwu
>
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