Evidence map›Paper›PMID 25238944›Full record

ArticleGenetica2014

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

Géraud Gourjon, Bérengère Saliba-Serre, Anna Degioanni

Abstract read
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In one paragraph

Article in Genetica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Géraud GourjonCNRS, MCC - MMSH, LAMPEA UMR 7269, Aix-Marseille Université, 5 rue du Château de l'Horloge, BP 647, 13094, Aix-en-Provence Cedex 2, France, ggourjon@hotmail.com.
Bérengère Saliba-Serre
Anna Degioanni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsModels, GeneticPolymorphism, Single NucleotideComputer SimulationGene FlowGene FrequencyGene PoolGenetic DriftGenetics, PopulationHumansMutation Rate

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.