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 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. 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 individuals resulting from admixture between Populus trichocarpa and Populus balsamifera and lengths of ancestry tracts indicate that admixture took place ~ 100 generations ago.We expect that providing a rapid and parameter-free software for local ancestry inference will make more accessible genomic studies about admixture processes.
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Molecular Biology and Evolution, Oxford University Press (OUP), 2018, 35 (9), pp.2318 - 2326. 〈10.1093/molbev/msy126〉
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Soumis le : lundi 27 août 2018 - 10:28:49
Dernière modification le : vendredi 26 octobre 2018 - 17:12:02

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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, 35 (9), pp.2318 - 2326. 〈10.1093/molbev/msy126〉. 〈hal-01630228v3〉

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