Abstract
The study of a disease using genetic identification has become possible by using haplotype information. The expectation-maximization algorithms are the standard approach in haplotype analysis. These approaches maximize the likelihood function of a genotypic distribution assuming Hardy-Weinberg equilibrium. However, these methods are time-consuming when applied to the sequence of many loci. In this study, we used a genetic algorithm to obtain the haplotype frequencies from the frequencies of genotypes.
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Drysdale CM, NcGraw DW, Stack CB (2006) Complex promoter and coding region β2-adrenergic receptor haplotypes alter receptor expression and predict in vivo responsiveness. Proc Nat Acad Sci USA 10483–10488
Niu T, Qin ZS, Xu X (2002) Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. Am J Hum Genet 70:157–169
Clark AG (1990) Inference of haplotypes from PCR-amplified samples of diploid populations. Mol Biol Evolut 7:111–122
Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68:978–989
Ziegler A, König IR (2006) A statistical approach to genetic epidemiology. Wiley-VCH, Weinheim, pp 243–250
Zhang J, Vingron M, Hoehe MR (2004) Haplotype reconstruction for diploid populations. Hum Hered 59:144–156
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This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008
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Azuma, R., Sakamoto, M. & Furutani, H. Haplotype estimation from genotypical data by genetic algorithm. Artif Life Robotics 13, 535–537 (2009). https://doi.org/10.1007/s10015-008-0606-5
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DOI: https://doi.org/10.1007/s10015-008-0606-5