Resample Methods for Testing Genomic Region Significance

• Activity Number: 248
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): David Swanson*+ and Christoph Lange
• Companies: Harvard University and Harvard School of Public Health
• Keywords: genetics ; permutation tests ; resample

Abstract

The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings.  Because of the importance and relative simplicity of analyzing these associations, many statistical methods have been devoted to them.  However, fewer methods have attempted to associate entire genes or genomic regions with outcomes, which is potentially more useful knowledge from a biological perspective.  We develop a method for quantifying the degree of association between a genomic region and outcome by generating hypothetical outcomes based on a "resample' model.  We then associate the region with observed outcomes using parametric tests.  We compare our method with permutation tests and other existing methods for associating genes and haplotypes with outcomes. The power of the method is less sensitive to the LD structure of the genomic region than other analysis methods.