Hi 
   
  I have been working with comparative genomic hybridization data for 4 years related to the genomics of AML.  I submitted a manuscript (on Tuesday) that outlines an approach based on statistical process control for analyzing this data.  In this framework we are able to analyze 2.1 million probe nimblegen arrays rapidly.
   
  I cannot circulate the manuscript now (it's under review) but would encourage anyone working with CGH data to look into process control methods.  This is a vast set of tools from industrial statistics (think Deming) that fit the CGH data framework ideally -- 2 copies of a gene is in cotrol and amplifications/deletions are out of control.
   
  I submittred my manuscript as an invited paper to a new excellent journal that I suggest you consider for your papers:  http://www.wiley.com/WileyCDA/WileyTitle/productCd-SAM.html  It is focused on applications and I think will be an excellent venue for the type of work and problems discussed on this list.
   
  Bill Shannon, PhD
BioRankings, LLC
Founder and President
314-704-8725 
http://BioRankings.com
   
  "Helping you gain understanding of statistical data to protect your investment."
   
  Associate Professor of Biostatistics in Medicine
Washington University School of Medicine
http://ilya.wustl.edu/~shannon


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