Open Access
June 2014 Leveraging local identity-by-descent increases the power of case/control GWAS with related individuals
Joshua N. Sampson, Bill Wheeler, Peng Li, Jianxin Shi
Ann. Appl. Stat. 8(2): 974-998 (June 2014). DOI: 10.1214/14-AOAS715


Large case/control Genome-Wide Association Studies (GWAS) often include groups of related individuals with known relationships. When testing for associations at a given locus, current methods incorporate only the familial relationships between individuals. Here, we introduce the chromosome-based Quasi Likelihood Score (cQLS) statistic that incorporates local Identity-By-Descent (IBD) to increase the power to detect associations. In studies robust to population stratification, such as those with case/control sibling pairs, simulations show that the study power can be increased by over 50%. In our example, a GWAS examining late-onset Alzheimer’s disease, the $p$-values among the most strongly associated SNPs in the APOE gene tend to decrease, with the smallest $p$-value decreasing from $1.23\times10^{-8}$ to $7.70\times10^{-9}$. Furthermore, as a part of our simulations, we reevaluate our expectations about the use of families in GWAS. We show that, although adding only half as many unique chromosomes, genotyping affected siblings is more efficient than genotyping randomly ascertained cases. We also show that genotyping cases with a family history of disease will be less beneficial when searching for SNPs with smaller effect sizes.


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Joshua N. Sampson. Bill Wheeler. Peng Li. Jianxin Shi. "Leveraging local identity-by-descent increases the power of case/control GWAS with related individuals." Ann. Appl. Stat. 8 (2) 974 - 998, June 2014.


Published: June 2014
First available in Project Euclid: 1 July 2014

zbMATH: 06333784
MathSciNet: MR3262542
Digital Object Identifier: 10.1214/14-AOAS715

Keywords: case–control , cQLS , GWAS , related individuals

Rights: Copyright © 2014 Institute of Mathematical Statistics

Vol.8 • No. 2 • June 2014
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