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자료유형
학술저널
저자정보
Song, Hae-Hiang (Division of Biostatistics, Department of Medical Lifescience, The Catholic University of Korea, College of Medicine) Hu, Hae-Jin (Department of Microbiology, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine) Seok, In-Hae (Department of Statistics, Hankuk University of Foreign Studies) Chung, Yeun-Jun (Department of Microbiology, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine)
저널정보
한국유전체학회 Genomics & informatics Genomics & informatics 제10권 제2호
발행연도
2012.1
수록면
81 - 87 (7page)

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Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional $F_{ST}$ measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the $F_{ST}$ estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific $F_{ST}$ and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.

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