Assessing population differentiation and isolation from single-nucleotide polymorphism data

We introduce a new, hierarchical, model for single-nucleotide polymorphism allele frequencies in a structured population, which is naturally fitted via Markov chain Monte Carlo methods. There is one parameter for each population, closely analogous to a population-specific version of Wright's FS...

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Vydáno v:	Journal of the Royal Statistical Society. Series B, Statistical methodology Ročník 64; číslo 4; s. 695 - 715
Hlavní autoři:	Nicholson, George, Smith, Albert V., Jónsson, Frosti, Gústafsson, Ómar, Stefánsson, Kári, Donnelly, Peter
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford, UK Blackwell Publishers 01.10.2002 Blackwell Royal Statistical Society
Edice:	Journal of the Royal Statistical Society Series B
Témata:	Bayes estimators Biological and medical sciences Bottleneck Chromosomes Coalescent Datasets Demography Estimation Estimators Exact sciences and technology Fixation indices Forensic genetics France Fundamental and applied biological sciences. Psychology Gene frequency General aspects Genetic loci Human genetics Iceland Inference from stochastic processes; time series analysis Markov chain Monte Carlo methods Markov processes Markovian processes Mathematics Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Monte Carlo simulation Population Population genetics Population histories Population parameters Probability and statistics Probability theory and stochastic processes Sciences and techniques of general use Statistical methods Statistical models Statistics Sufficiency and information U.S.A Utah United States Europe America France North America Atlantic Ocean Islands Iceland Utah Human Bottleneck Stochastic model Monte Carlo method Parameter estimation Demography Index History Population genetics Markov chain Statistical method Fixation Wright Fisher diffusion Genetics Hierarchical model Population dynamics Diffusion Differentiation Fixation index Population history
ISSN:	1369-7412, 1467-9868
On-line přístup:	Získat plný text
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