Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data
Summary 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...
Published in: | Journal of the Royal Statistical Society Series B: Statistical Methodology |
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Oxford University Press (OUP)
2002
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Online Access: | http://dx.doi.org/10.1111/1467-9868.00357 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F1467-9868.00357 https://academic.oup.com/jrsssb/article-pdf/64/4/695/49723496/jrsssb_64_4_695.pdf |
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croxfordunivpr:10.1111/1467-9868.00357 2024-09-15T18:14:13+00:00 Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data Nicholson, George Smith, Albert V. Jónsson, Frosti Gústafsson, Ómar Stefánsson, Kári Donnelly, Peter UK Engineering and Physical Sciences Research Council Biotechnology and Biological Sciences Research Council University of Chicago 2002 http://dx.doi.org/10.1111/1467-9868.00357 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F1467-9868.00357 https://academic.oup.com/jrsssb/article-pdf/64/4/695/49723496/jrsssb_64_4_695.pdf en eng Oxford University Press (OUP) https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model Journal of the Royal Statistical Society Series B: Statistical Methodology volume 64, issue 4, page 695-715 ISSN 1369-7412 1467-9868 journal-article 2002 croxfordunivpr https://doi.org/10.1111/1467-9868.00357 2024-08-12T04:26:56Z Summary 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 FST, which can be interpreted as measuring how isolated the relevant population has been. Our model includes the effects of single-nucleotide polymorphism ascertainment and is motivated by population genetics considerations, explicitly in the transient setting after divergence of populations, rather than as the equilibrium of a stochastic model, as is traditionally the case. For the sizes of data set that we consider the method provides good parameter estimates and considerably outperforms estimation methods analogous to those currently used in practice. We apply the method to one new and one existing human data set, each with rather different characteristics—the first consisting of three rather close European populations; the second of four populations taken from across the globe. A novelty of our framework is that the fit of the underlying model can be assessed easily, and these results are encouraging for both data sets analysed. Our analysis suggests that Iceland is more differentiated than the other two European populations (France and Utah), a finding which is consistent with the historical record, but not obvious from comparisons of simple summary statistics. Article in Journal/Newspaper Iceland Oxford University Press Journal of the Royal Statistical Society Series B: Statistical Methodology 64 4 695 715 |
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Open Polar |
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Oxford University Press |
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croxfordunivpr |
language |
English |
description |
Summary 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 FST, which can be interpreted as measuring how isolated the relevant population has been. Our model includes the effects of single-nucleotide polymorphism ascertainment and is motivated by population genetics considerations, explicitly in the transient setting after divergence of populations, rather than as the equilibrium of a stochastic model, as is traditionally the case. For the sizes of data set that we consider the method provides good parameter estimates and considerably outperforms estimation methods analogous to those currently used in practice. We apply the method to one new and one existing human data set, each with rather different characteristics—the first consisting of three rather close European populations; the second of four populations taken from across the globe. A novelty of our framework is that the fit of the underlying model can be assessed easily, and these results are encouraging for both data sets analysed. Our analysis suggests that Iceland is more differentiated than the other two European populations (France and Utah), a finding which is consistent with the historical record, but not obvious from comparisons of simple summary statistics. |
author2 |
UK Engineering and Physical Sciences Research Council Biotechnology and Biological Sciences Research Council University of Chicago |
format |
Article in Journal/Newspaper |
author |
Nicholson, George Smith, Albert V. Jónsson, Frosti Gústafsson, Ómar Stefánsson, Kári Donnelly, Peter |
spellingShingle |
Nicholson, George Smith, Albert V. Jónsson, Frosti Gústafsson, Ómar Stefánsson, Kári Donnelly, Peter Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data |
author_facet |
Nicholson, George Smith, Albert V. Jónsson, Frosti Gústafsson, Ómar Stefánsson, Kári Donnelly, Peter |
author_sort |
Nicholson, George |
title |
Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data |
title_short |
Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data |
title_full |
Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data |
title_fullStr |
Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data |
title_full_unstemmed |
Assessing Population Differentiation and Isolation from Single-Nucleotide Polymorphism Data |
title_sort |
assessing population differentiation and isolation from single-nucleotide polymorphism data |
publisher |
Oxford University Press (OUP) |
publishDate |
2002 |
url |
http://dx.doi.org/10.1111/1467-9868.00357 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F1467-9868.00357 https://academic.oup.com/jrsssb/article-pdf/64/4/695/49723496/jrsssb_64_4_695.pdf |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Journal of the Royal Statistical Society Series B: Statistical Methodology volume 64, issue 4, page 695-715 ISSN 1369-7412 1467-9868 |
op_rights |
https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model |
op_doi |
https://doi.org/10.1111/1467-9868.00357 |
container_title |
Journal of the Royal Statistical Society Series B: Statistical Methodology |
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64 |
container_issue |
4 |
container_start_page |
695 |
op_container_end_page |
715 |
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1810451995699445760 |