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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of the Royal Statistical Society. Series B, Statistical methodology Jg. 64; H. 4; S. 695 - 715
Hauptverfasser: Nicholson, George, Smith, Albert V., Jónsson, Frosti, Gústafsson, Ómar, Stefánsson, Kári, Donnelly, Peter
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford, UK Blackwell Publishers 01.10.2002
Blackwell
Royal Statistical Society
Schriftenreihe:Journal of the Royal Statistical Society Series B
Schlagworte:
ISSN:1369-7412, 1467-9868
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie:istex:C016FA08358780794850850CEA1DEF452699E51C
ark:/67375/WNG-DW0NR729-5
ArticleID:RSSB357
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1369-7412
1467-9868
DOI:10.1111/1467-9868.00357