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This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

Open Access Proceedings

An aggregating U-Test for a genetic association study of quantitative traits

Ming Li, Wenjiang Fu and Qing Lu*

Author Affiliations

1Department of Epidemiology, Michigan State University, B601 West Fee Hall, East Lansing, MI 48824, USA

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BMC Proceedings 2011, 5(Suppl 9):S23  doi:10.1186/1753-6561-5-S9-S23

Published: 29 November 2011

Abstract

We propose a novel aggregating U-test for gene-based association analysis. The method considers both rare and common variants. It adaptively searches for potential disease-susceptibility rare variants and collapses them into a single “supervariant.” A forward U-test is then used to assess the joint association of the supervariant and other common variants with quantitative traits. Using 200 simulated replicates from the Genetic Analysis Workshop 17 mini-exome data, we compare the performance of the proposed method with that of a commonly used approach, QuTie. We find that our method has an equivalent or greater power than QuTie to detect nine genes that influence the quantitative trait Q1. This new approach provides a powerful tool for detecting both common and rare variants associated with quantitative traits.