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This article is part of the supplement: Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci

Open Access Open Badges Proceedings

Detecting epistatic interactions contributing to human gene expression using the CEPH family data

Hua Li1*, Guimin Gao2, Jian Li3, Grier P Page2 and Kui Zhang2

Author Affiliations

1 Bioinformatics Center, Stowers Institute for Medical Research, 1000 East 50th Street, Kansas City, Missouri 64110, USA

2 Section on Statistical Genetics, Department of Biostatistics, RPHB 327, 1530 3rd Avenue South, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA

3 Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA

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BMC Proceedings 2007, 1(Suppl 1):S67  doi:

Published: 18 December 2007


It is believed that epistatic interactions among loci contribute to variations in quantitative traits. Several methods are available to detect epistasis using population-based data. However, methods to characterize epistasis for quantitative traits in family-based association analysis are not well developed, especially for studying thousands of gene expression traits. Here, we proposed a linear mixed-model approach to detect epistasis for quantitative traits using family data. The proposed method was implemented in a widely used software program SOLAR. We evaluated the power of the method by simulation studies and applied this method to the analysis of the Centre d'Etude du Polymorphisme Humain family gene expression data provided by Genetics Analysis Workshop 15 (GAW15).