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Computational and Experimental Approaches to Reveal the Effects of Single Nucleotide Polymorphisms with Respect to Disease Diagnostics
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Int. J. Mol. Sci. 2014, 15(6), 10724-10737; doi:10.3390/ijms150610724

Weighted Risk Score-Based Multifactor Dimensionality Reduction to Detect Gene-Gene Interactions in Nasopharyngeal Carcinoma

1
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
2
State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
3
Department of Information Technology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
*
Authors to whom correspondence should be addressed.
Received: 4 March 2014 / Revised: 21 April 2014 / Accepted: 3 June 2014 / Published: 13 June 2014
(This article belongs to the Collection Human Single Nucleotide Polymorphisms and Disease Diagnostics)
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Abstract

Determining the complex relationships between diseases, polymorphisms in human genes and environmental factors is challenging. Multifactor dimensionality reduction (MDR) has been proven to be capable of effectively detecting the statistical patterns of epistasis, although classification accuracy is required for this approach. The imbalanced dataset can cause seriously negative effects on classification accuracy. Moreover, MDR methods cannot quantitatively assess the disease risk of genotype combinations. Hence, we introduce a novel weighted risk score-based multifactor dimensionality reduction (WRSMDR) method that uses the Bayesian posterior probability of polymorphism combinations as a new quantitative measure of disease risk. First, we compared the WRSMDR to the MDR method in simulated datasets. Our results showed that the WRSMDR method had reasonable power to identify high-order gene-gene interactions, and it was more effective than MDR at detecting four-locus models. Moreover, WRSMDR reveals more information regarding the effect of genotype combination on the disease risk, and the result was easier to determine and apply than with MDR. Finally, we applied WRSMDR to a nasopharyngeal carcinoma (NPC) case-control study and identified a statistically significant high-order interaction among three polymorphisms: rs2860580, rs11865086 and rs2305806. View Full-Text
Keywords: gene-gene interaction; weighted risk score; multifactor dimensionality reduction; nasopharyngeal carcinoma gene-gene interaction; weighted risk score; multifactor dimensionality reduction; nasopharyngeal carcinoma
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Li, C.-F.; Luo, F.-T.; Zeng, Y.-X.; Jia, W.-H. Weighted Risk Score-Based Multifactor Dimensionality Reduction to Detect Gene-Gene Interactions in Nasopharyngeal Carcinoma. Int. J. Mol. Sci. 2014, 15, 10724-10737.

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