Combining effects from rare and common genetic variants in an exome-wide association study of sequence data

BMC Proceedings

Proceedings

Vincent Carey¹  Weiliang Qiu¹  Michael H Cho¹  Hugues Aschard²  Bogdan Pasaniuc²  Noah Zaitlen² 

[1] Channing Laboratory, Brigham and Women’s Hospital, 181 Longwood Avenue, 02115, Boston, MA, USA;Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, 02115, Boston, MA, USA;

关键词: Common Variant;    Rare Variant;    Causal Gene;    Causal Variant;    Genetic Analysis Workshop;   

DOI  :  10.1186/1753-6561-5-S9-S44

来源: Springer

【 摘 要 】

Recent breakthroughs in next-generation sequencing technologies allow cost-effective methods for measuring a growing list of cellular properties, including DNA sequence and structural variation. Next-generation sequencing has the potential to revolutionize complex trait genetics by directly measuring common and rare genetic variants within a genome-wide context. Because for a given gene both rare and common causal variants can coexist and have independent effects on a trait, strategies that model the effects of both common and rare variants could enhance the power of identifying disease-associated genes. To date, little work has been done on integrating signals from common and rare variants into powerful statistics for finding disease genes in genome-wide association studies. In this analysis of the Genetic Analysis Workshop 17 data, we evaluate various strategies for association of rare, common, or a combination of both rare and common variants on quantitative phenotypes in unrelated individuals. We show that the analysis of common variants only using classical approaches can achieve higher power to detect causal genes than recently proposed rare variant methods and that strategies that combine association signals derived independently in rare and common variants can slightly increase the power compared to strategies that focus on the effect of either the rare variants or the common variants.

【 授权许可】

CC BY   
© Aschard et al; licensee BioMed Central Ltd. 2011