Open Access
May 2014 Pooled Association Tests for Rare Genetic Variants: A Review and Some New Results
Andriy Derkach, Jerry F. Lawless, Lei Sun
Statist. Sci. 29(2): 302-321 (May 2014). DOI: 10.1214/13-STS456

Abstract

In the search for genetic factors that are associated with complex heritable human traits, considerable attention is now being focused on rare variants that individually have small effects. In response, numerous recent papers have proposed testing strategies to assess association between a group of rare variants and a trait, with competing claims about the performance of various tests. The power of a given test in fact depends on the nature of any association and on the rareness of the variants in question. We review such tests within a general framework that covers a wide range of genetic models and types of data. We study the performance of specific tests through exact or asymptotic power formulas and through novel simulation studies of over 10,000 different models. The tests considered are also applied to real sequence data from the 1000 Genomes project and provided by the GAW17. We recommend a testing strategy, but our results show that power to detect association in plausible genetic scenarios is low for studies of medium size unless a high proportion of the chosen variants are causal. Consequently, considerable attention must be given to relevant biological information that can guide the selection of variants for testing.

Citation

Download Citation

Andriy Derkach. Jerry F. Lawless. Lei Sun. "Pooled Association Tests for Rare Genetic Variants: A Review and Some New Results." Statist. Sci. 29 (2) 302 - 321, May 2014. https://doi.org/10.1214/13-STS456

Information

Published: May 2014
First available in Project Euclid: 18 August 2014

zbMATH: 1332.62410
MathSciNet: MR3264544
Digital Object Identifier: 10.1214/13-STS456

Keywords: complex traits , linear statistics , next generation sequencing , power , quadratic statistics , score tests , weighting

Rights: Copyright © 2014 Institute of Mathematical Statistics

Vol.29 • No. 2 • May 2014
Back to Top