Reconstructing past history from whole-genomes: an ABC approach handling recombining data.

Flora Jay 1, 2, 3 Simon Boitard 4 Frederic Austerlitz 5, 6
1 BioInfo - LRI - Bioinformatique (LRI)
LRI - Laboratoire de Recherche en Informatique
3 TAU - TAckling the Underspecified
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : In population genetics, a key interest is to reconstruct the demographic history of a population using its genetic data. This history can be characterized by multiple events such as migration of individuals, admixture with another population, or changes in population size. With the availability of large-scale genomic data numerous methods have arisen for untangling complicated histories or retrieving a detailed picture of a population at different time periods. Although genomes are known to be extremely informative about demography, there are many ways to extract this information. We present an approach designed for inferring past population sizes for an intermediate number of fully sequenced genomes. It relies on Approximate Bayesian Computation (ABC), a simulation-based statistical framework for generic model comparison and parameter inference. We demonstrated how the specificities of DNA sequencing data (namely haplotypic information, long range genetic correlation and genotyping errors) can be handled using ABC and fast genetic simulators, and further infer histories of successive bottleneck and expansions in human populations.
Type de document :
Communication dans un congrès
European Mathematical Genetics Meeting, Apr 2017, Tartu, Estonia
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https://hal.archives-ouvertes.fr/hal-01679379
Contributeur : Flora Jay <>
Soumis le : mardi 9 janvier 2018 - 19:03:34
Dernière modification le : mardi 8 janvier 2019 - 08:36:01

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  • HAL Id : hal-01679379, version 1

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Flora Jay, Simon Boitard, Frederic Austerlitz. Reconstructing past history from whole-genomes: an ABC approach handling recombining data.. European Mathematical Genetics Meeting, Apr 2017, Tartu, Estonia. 〈hal-01679379〉

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