Browse > Article
http://dx.doi.org/10.5351/KJAS.2011.24.5.861

Exploration of the Gene-Gene Interactions Using the Relative Risks in Distinct Genotypes  

Jung, Ji-Won (Biotoxtech, Inc.)
Yee, Jae-Yong (Department of Physiology and Biophysics, Eulji University)
Lee, Suk-Hoon (Department of Statistics, Chungnam National University)
Pa, Mi-Ra (Department of Preventive Medicine, Eulji University)
Publication Information
The Korean Journal of Applied Statistics / v.24, no.5, 2011 , pp. 861-869 More about this Journal
Abstract
One of the main objects of recent genetic studies is to understand genetic factors that induce complex diseases. If there are interactions between loci, it is difficult to find such associations through a single-locus analysis strategy. Thus we need to consider the gene-gene interactions and/or gene-environment interactions. The MDR(multifactor dimensionality reduction) method is being used frequently; however, it is not appropriate to detect interactions caused by a small fraction of the possible genotype pairs. In this study, we propose a relative risk interaction explorer that detects interactions through the calculation of the relative risks between the control and disease groups from each genetic combinations. For illustration, we apply this method to MDR open source data. We also compare the MDR and the proposed method using the simulated data eight genetic models.
Keywords
Gene-gene interaction; relative risk; genetic model; MDR;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Ritchie, M. D., Hahn, L. W., Roodi, N., Bailey, L. R., Dupont, W. D., Parl, F. F. and Moore, J. H. (2001). Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer, The American Society of Human Genetics, 69, 138-147.   DOI   ScienceOn
2 Zelen, M. (1971). The analysis of several 2 ${\times}$ 2 contingency tables, Biometrika, 58, 129-137.
3 Chung, Y., Lee, S. Y., Elston, R. C. and Park, T. (2007). Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions, Bioninformatics, 23, 71-76.   DOI   ScienceOn
4 Cordell, H. J. (2009). Detecting gene-gene interactions that underlie human diseases, Nature Reviews Genetics, 10, 392-404.
5 Dong, C., Chu, X., Wang, Y., Jin, L., Shi, T., Huang, W. and Li, Y. (2008). Exploration of gene-gene interaction effects using entropy-based methods, European Journal of Human Genetics, 16, 229-235.   DOI   ScienceOn
6 Heidema, A. G., Boer, J. M. A., Nagelkerke, N., Mariman, E. C. M., Van der, A, D. L. and Feskens, E. J. M. (2006). The challenge for genetic epidemiologists: How to analyze large numbers of SNPs in relation to complex diseases, BMC Genetics, 7, 1-15.
7 Lee, S. Y., Chung, Y., Elston, R. C., Kim, Y. and Park, T. (2007). Log-linear model-based multifactor dimensionality reduction method to detect gene-gene interactions, Bioinformatics, 23, 2589-2595.   DOI   ScienceOn
8 Namkung, J., Elston, R. C., Yang, J. M. and Park, T. (2009). Identification of gene-gene interactions in the presence of missing data using the multifactor dimensionality reduction method, Genetic Epidemiology, 33, 646-656.   DOI   ScienceOn
9 Lou, X. Y., Chen, G. B., Yan, L., Ma, J. Z., Zhu, J., Elston, R. C. and Li, M. D. (2007). A generalized combinatorial approach for detecting gene-by-gene and gene-by-environment interactions with application to nicotine dependence, The American Journal of Human Genetics, 80, 1125-1137.   DOI   ScienceOn
10 Lou, X. Y., Chen, G. B., Yan, L., Ma, J. Z., Mangold, J. E., Zhu, J., Elston, R. C. and Li, M. D. (2008). A combinatorial approach to detecting gene-gene and gene-environment interactions in family studies, The American Journal of Human Genetics, 83, 457-467.   DOI   ScienceOn
11 Agresti, A. (1992). A survey if exact inference for contingency tables, Statistical Science, 7, 131-153.   DOI   ScienceOn