More Efficient Experimental Designs for CNV Studies Utilizing aCGH Technology

• Activity Number: 125
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Jeanette Eckel-Passow*+ and Shannon McDonnell and Shaun Riska and Erik Thorland and Eric Klee
• Companies: Mayo Clinic and Mayo Clinic and Mayo Clinic and Mayo Clinic and Mayo Clinic
• Keywords: genetics ; cancer ; microarray

Abstract

Improvements in the methods used for the detection of segments of DNA amplification and deletion will significantly benefit copy number variation (CNV) studies. We evaluated the reference design to determine if this design could be augmented to optimize the process without affecting the results. Most CNV detection methods use microarray based technologies that output relative intensity values rather than absolute copy number (CN), necessitating the use of a baseline sample to estimate CN. Most protocols utilizing array comparative genomic hybridization necessitate a reference sample be hybridized to every array to provide a baseline for CN estimation. Using two cancer data sets, we empirically demonstrate that more efficient designs can be considered that require significantly fewer arrays, while maintaining the accuracy and precision to that obtained with the standard reference design.