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http://dx.doi.org/10.7465/jkdi.2012.23.3.467

Major gene interaction identification in Hanwoo by adjusted environmental effects  

Lee, Jea-Young (Department of Statistics, Yeungnam University)
Jin, Mi-Hyun (Department of Statistics, Yeungnam University)
Publication Information
Journal of the Korean Data and Information Science Society / v.23, no.3, 2012 , pp. 467-474 More about this Journal
Abstract
Human diseases and livestock economic traits are not typically the result of variation of a single genetic locus, but are rather the result of interplay between interactions among multiple genes and a variety of environmental exposures. We have used linear regression model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. Of course, we use 5 SNPs (single uncleotide polymorphism) which were studied recently by Oh et al. (2011). We apply the MDR (multifactor demensionality reduction) method on the identify major interaction effects of single nucleotide polymorphisms responsible for economic traits in a Korean cattle population.
Keywords
Gene interaction; genotype; mutifactor dimensionality reduction; single nucleotide polymorphism;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 Good, P. (2000). Permutation test : A practical guide to resampling methods for testing hypotheses, Springer-Verlag, New York.
2 Lee, J. Y., Kwon, J. C. and Kim, J. J. (2008). Multifactor dimensionality reduction(MDR) analysis to detect single nucleotide polymorphisms associated with a carcass trait in a Hanwoo population. Asian- Australasian Journal of Animal Sciences, 21, 784-788.   DOI
3 Lee, J. Y. and Lee, J. H. (2010). Support vector machine and multifactor dimensionality reduction for detecting major gene interactions of continuous data. Journal of the Korean Data & Information Science Society, 21, 1271-1280.
4 Lee, J. Y., Lee, J. H. and Lee, Y. W. (2010). Detection of major genotype combination by genotype matrix. Journal of the Korean Data & Information Science Society, 21, 387-395.
5 Lee, Y. S., Oh, D. Y. and Yeo, J. S. (2011). Study on identification of candidate DNA marker related with beef quality in QTL region of BTA 2 in Hanwoo population. Journal of the Korean Data & Information Science Society, 22, 661-669.
6 Matsuhashi. T., Maruyama. S., Uemoto. Y., Kobayashi. N., Mannen. H., Abe. T., Sakaguchi. S. and Kobayashi. E. (2011). Effects of bovine fatty acid synthase, stearoyl-coenzyme A desaturase, sterol regulatory element-binding protein 1, and growth ghormone gene polymorphisms on fatty acid composition and carcass traits in Japanese Black cattle. Journal of Animal Science, 89, 12-22.   DOI   ScienceOn
7 Oh, D. Y., Lee, Y. S., La, B. M., Yeo, J. S., Chung, E. Y., Kim, Y. Y. and Lee, C. Y. (2011). Fatty acid composition of beef is associated with exonic nucleotide variants of the gene encoding FASN. Molecular Biology Reports, 39, 4083-4090.
8 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. American Journal of Human Genetics, 69, 138-147.   DOI   ScienceOn
9 Velez, D. R., White, B. C., Motsinger, A. A., Bush, W. S., Ritchie, M. D., Williams, S. M. and Moore, J. H. (2007). A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction. Genetic Epidemiology, 31, 306-315.   DOI   ScienceOn
10 Casas, E., White, S. N., Riley, D. G., Smith, T. P. L., Brenneman, R. A., Olson, T.A., Johnson, D. D., Coleman, S. W., Bennett, G. L. and Chase, C. C. (2005). Assessment of single nucleotide polymorphisms in genes residing on choromosomes 14 and 29 for association with carcass composition traits in Bos indicus cattle. Journal of Animal Science, 83, 13-19.   DOI