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Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies

Morris, A., Pedder, A. and Ayres, K. (2003) Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies. Genetic Epidemiology, 25 (2). pp. 106-114. ISSN 0741-0395

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To link to this item DOI: 10.1002/gepi.10254


Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particulary in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process. Genet Epidemiol 25:106-114, 2003. (C) 2003 Wiley-Liss, Inc.

Item Type:Article
Divisions:Faculty of Life Sciences > School of Biological Sciences
ID Code:10823
Uncontrolled Keywords:linkage disequilibrium, Bayesian, Markov chain Monte Carlo, SNP, haplotypes, SINGLE-NUCLEOTIDE POLYMORPHISMS, HUMAN GENOME, MAXIMUM-LIKELIHOOD, POPULATION, SELECTION, MAP

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