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