Loter: A software package to infer local ancestry for a wide range of species

Abstract : Admixture between populations provides opportunity to study biological adaptation and phenotypic variation. Admixture studies can rely on local ancestry inference for admixed individuals, which consists of computing at each locus the number of copies that originate from ancestral source populations. Existing software packages for local ancestry inference are tuned to provide accurate results on human data and recent admixture events. Here, we introduce Loter, an open-source software package that does not require any biological parameter besides haplotype data in order to make local ancestry inference available for a wide range of species. Using simulations, we compare the performance of Loter to HAPMIX, LAMP-LD, and RFMix. HAPMIX is the only software severely impacted by imperfect haplotype reconstruction. Loter is the less impacted software by increasing admixture time when considering simulated and admixed human genotypes. LAMP-LD and RFMIX are the most accurate method when admixture took place 20 generations ago or less; Loter accuracy is comparable or better than RFMix accuracy when admixture took place of 50 or more generations; and its accuracy is the largest when admixture is more ancient than 150 generations. For simulations of admixed Populus genotypes, Loter and LAMP-LD are robust to increasing admixture times by contrast to RFMix. When comparing length of reconstructed and true ancestry tracts, Loter and LAMP-LD provide results whose accuracy is again more robust than RFMix to increasing admixture times. We apply Loter to admixed Populus individuals and lengths of ancestry tracts indicate that admixture took place around 100 generations ago.
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Contributeur : Julien Mairal <>
Soumis le : vendredi 22 juin 2018 - 13:24:41
Dernière modification le : mercredi 6 février 2019 - 11:46:04
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Thomas Dias-Alves, Julien Mairal, Michael Blum. Loter: A software package to infer local ancestry for a wide range of species. Molecular Biology and Evolution, Oxford University Press (OUP), 2018, 〈10.1093/molbev/msy126〉. 〈hal-01630228v2〉



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