This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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132
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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Abstract - #309035 |
Title:
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Analysis of Untyped SNPs: Maximum Likelihood and Single Imputation Methods
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Author(s):
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Yijuan Hu*+ and Danyu Lin
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Companies:
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The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
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Address:
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3104 McGavran-Greenberg Hall, CB#7420, Chapel Hill, NC, 27599-7420,
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Keywords:
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association studies ;
retrospective likelihood ;
single nucleotide polymorphisms ;
genotype ;
haplotype
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Abstract:
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Although the rapid improvement and reduced cost of high-throughput genotyping have enabled many SNPs to be genotyped in genome-wide association studies, untyped SNPs are still of importance. We examine the properties and performance of two classes of methods. The first class computes maximum-likelihood estimates for models of the joint distribution of the phenotype and the observed genotypes. The second is a two-stage single imputation approach. Simulation studies demonstrated that the maximum-likelihood approach performs well and is generally more powerful than imputation, whereas imputation often yielded biased estimates of effects and underestimation of variances. Theoretical derivations revealed a novel finding that all imputation methods have correct type I error in testing the single-SNP effect. Illustration with a genome-wide association study is provided.
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Authors who are presenting talks have a * after their name.
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