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Activity Number: 440
Type: Contributed
Date/Time: Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305293
Title: A Score-Based Combinatorial Approach to Detecting Gene-Gene Interactions in Nuclear Families
Author(s): Xiaoqi Cui*+ and Huann-Sheng Chen
Companies: Michigan Technological University and Michigan Technological University
Address: Math Dept, 1400 Townsend Drive, Houghton, MI, 49931,
Keywords: gene-gene interaction ; MDR ; score ; nuclear family ; likelihood
Abstract:

Modern genetic epidemiology is an interdisciplinary subject, which often uses statistical tools to find out the relationships between disease traits and the underlying genetic characteristics. Common complex human diseases are the result of interactions of several genes instead of the effect of a single gene. To detect gene-gene interactions, we proposed a new score based combinatorial method which is an important modification and extension of the current Multifactor-Dimensionality Reduction (MDR)* method. Our approach can deal with family data, and improve computational efficiency by incorporating a likelihood score. In simulation, we will compare our method with several current ones.

*Marylyn D. Ritchie, et al.: Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer. Am. J. Hum. Genet 2001, 69: 138-147

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