title: Admixture Indicative Interval (AII): a new approach to assess trends in genetic admixture.
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.
authors.affiliation: CNRS, 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.
authors.forename: Géraud
authors.initials: G
authors.lastname: Gourjon
authors.forename: Bérengère
authors.initials: B
authors.lastname: Saliba-Serre
authors.forename: Anna
authors.initials: A
authors.lastname: Degioanni
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D051456:Gene Flow; D005787:Gene Frequency; D005788:Gene Pool; D040961:Genetic Drift; D005828:Genetics, Population / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D008957:Models, Genetic; D059645:Mutation Rate; D020641:Polymorphism, Single Nucleotide