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Abstract Details

Activity Number: 284
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #308951
Title: Evolutionary Clustering of SNP Haplotypes for Genomewide Association Studies
Author(s): Karin S. Dorman*+ and Wei-Chen Chen and Ranjan Maitra
Companies: Iowa State University and Iowa State University and Iowa State University
Address: Department of Statistics, Ames, IA, 50011,
Keywords: phylogenetics ; model-based clustering ; genome-wide association study ; SNP ; haplotype ; bootstrap
Abstract:

Association analysis is a powerful method to locate genes associated with phenotypic traits. With the advent of genomic SNP data, genome-wide association studies (GWAS) raise unprecedented risk of false discovery due to repeated statistical tests. Using multi-locus SNP haplotypes instead of single SNP loci can increase the power to detect association. Unfortunately, haplotype models are parameter-rich and difficult to estimate. One solution is to reduce the dimension by clustering the haplotypes into a relatively small collection of K ancestral types. We propose an evolution-based method for clustering haplotypes that uses our phyloclustering framework. A bootstrap technique is used to estimate K. Our method performs similar to a parsimony-based grouping strategy with information criterion to estimate K (Tzeng, 2005) and scales better to GWAS-style datasets.


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