JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 164
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305995
Title: Genetic Association Testing with Quantitative Traits in Samples with Pedigree and Population Structure
Author(s): Timothy Thornton*+
Companies: University of Washington
Address: Department of Biostatistics, Seattle, WA, 98195, United States
Keywords: GWAS ; Population Structure ; Quantitative Traits ; Pedigrees ; Association ; Relatedness

Genome-wide association studies (GWAS) are commonly used for the mapping of genetic loci that influence complex traits. The observations in GWAS can have several sources of dependence, including population structure and relatedness among the sample individuals, some of which might be know and some unknown. It is well known that failure to appropriately account for both pedigree and population structure can lead to spurious association and reduced power. We propose a novel method for association testing of quantitative traits in samples with partially or completely unknown population and pedigree structure. Features of the method include: (1) it is applicable and computationally feasible for a variety of study designs, ranging from studies that have a combination of unrelated individuals and small pedigrees, to studies of isolated founder populations; (2) it can incorporate phenotype information on relatives with missing genotype data; and (3) it is completely applicable to arbitrary phenotypes. We demonstrate the power and validity of the proposed method in simulation studies with related individuals and population structure, including admixture.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.