Literature DB >> 25238944

Admixture Indicative Interval (AII): a new approach to assess trends in genetic admixture.

Géraud Gourjon1, Bérengère Saliba-Serre, Anna Degioanni.   

Abstract

The genetic admixture is a dynamic and diachronic process, taking place during a great number of generations. Consequently, a sole admixture rate does not represent such an event and several estimates could help to take into account its dynamics. We developed an Admixture Indicative Interval (AII) which gives a mathematical key to avoid this problem by integrating several admixture estimators and their respective accuracy into a single metric and provides a trend in genetic admixture. To illustrate AIIs interests in admixture studies, AII were calculated using seven estimators on two sets of simulated SNPs data generated under two different admixture scenarios and were then calculated from several published admixed population data: a Comorian population and several Puerto-Rican and Colombian populations for recent admixture events as well as European populations representing the Neolithic/Paleolithic admixture for an older event. Our method provides intervals taking properly the variability and accuracy of admixture estimates into account. The AII lays in the intuitive interval in all actual and simulated datasets and is not biased by divergent points by the mean of a double-weighting step. The great quantity of heterogeneous parental contributions is synthesized by a few AII, which turn out to be more manageable and meaningful than aplenty variable point estimates. This offers an improvement in admixture study, allowing a better understanding of migratory flows. Furthermore, it offers a better assessment of admixture than the arithmetic mean, and enhances comparisons between regions, samples, and between studies on same population.

Mesh:

Year:  2014        PMID: 25238944     DOI: 10.1007/s10709-014-9792-3

Source DB:  PubMed          Journal:  Genetica        ISSN: 0016-6707            Impact factor:   1.082


  38 in total

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Authors:  J K Pritchard; M Stephens; P Donnelly
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2.  Estimation of admixture proportions: a likelihood-based approach using Markov chain Monte Carlo.

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3.  Admixture in Hispanics: distribution of ancestral population contributions in the Continental United States.

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4.  Maximum-likelihood estimation of admixture proportions from genetic data.

Authors:  Jinliang Wang
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5.  Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies.

Authors:  Daniel Falush; Matthew Stephens; Jonathan K Pritchard
Journal:  Genetics       Date:  2003-08       Impact factor: 4.562

6.  METHODS OF ANALYSIS OF THE GENETIC COMPOSITION OF A HYBRID POPULATION.

Authors:  D F ROBERTS; R W HIORNS
Journal:  Hum Biol       Date:  1965-02       Impact factor: 0.553

7.  The genetic structure of admixed populations.

Authors:  J C Long
Journal:  Genetics       Date:  1991-02       Impact factor: 4.562

8.  Bayesian analysis of an admixture model with mutations and arbitrarily linked markers.

Authors:  Laurent Excoffier; Arnaud Estoup; Jean-Marie Cornuet
Journal:  Genetics       Date:  2005-01-16       Impact factor: 4.562

9.  A coalescent-based estimator of admixture from DNA sequences.

Authors:  Jinliang Wang
Journal:  Genetics       Date:  2006-04-19       Impact factor: 4.562

10.  Racial admixture in north-eastern Brazil.

Authors:  H Krieger; N E Morton; M P Mi; E Azevêdo; A Freire-Maia; N Yasuda
Journal:  Ann Hum Genet       Date:  1965-11       Impact factor: 1.670

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