Unsupervised detection of ancestry tracks with the GHap r package

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorInternational Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics-
Autor(es): dc.contributorUniversità Cattolica del Sacro Cuore-
Autor(es): dc.contributorBOKU—University of Natural Resources and Life Sciences-
Autor(es): dc.creatorUtsunomiya, Yuri Tani [UNESP]-
Autor(es): dc.creatorMilanesi, Marco [UNESP]-
Autor(es): dc.creatorBarbato, Mario-
Autor(es): dc.creatorUtsunomiya, Adam Taiti Harth [UNESP]-
Autor(es): dc.creatorSölkner, Johann-
Autor(es): dc.creatorAjmone-Marsan, Paolo-
Autor(es): dc.creatorGarcia, José Fernando [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:32:19Z-
Data de disponibilização: dc.date.available2022-02-22T00:32:19Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1111/2041-210X.13467-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/201006-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/201006-
Descrição: dc.descriptionThe identification of ancestry tracks is a powerful tool to assist the inference of evolutionary events in the genomes of animals and plants. However, algorithms for ancestry track detection typically require labelled reference population data. This dependency prevents the analysis of genomic data lacking prior information on genetic structure, and may produce classification bias when samples in the reference data are inadvertently admixed. We combined heuristics with K-means clustering to deploy a method that can detect ancestry tracks without the provision of lineage labels for reference population data. The resulting algorithm uses phased genotypes to infer individual ancestry proportions and local ancestry. By piling up ancestry tracks across individuals, our method also allows for mapping loci with excess or deficit ancestry from specific lineages. Using both simulated and real genomic data, we found that the proposed method was accurate in inferring genetic structure, assigning chromosomal segments to lineages and estimating individual ancestry, especially in cases where ancestry tracks resulted from recent admixture of highly divergent lineages. The method is implemented as part of the v2 release of the GHap r package (available at https://cran.r-project.org/package=GHap and https://bitbucket.org/marcomilanesi/ghap/src/master/).-
Descrição: dc.descriptionDepartment of Support Production and Animal Health School of Veterinary Medicine of Araçatuba São Paulo State University (Unesp)-
Descrição: dc.descriptionInternational Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics-
Descrição: dc.descriptionDepartment of Animal Science Food and Nutrition—DIANA and Nutrigenomics and Proteomics Research Center Università Cattolica del Sacro Cuore-
Descrição: dc.descriptionDivision of Livestook Sciences Department of Sustainable Agriculture System BOKU—University of Natural Resources and Life Sciences-
Descrição: dc.descriptionDepartment of Preventive Veterinary Medicine and Animal Reproduction School of Agricultural and Veterinarian Sciences São Paulo State University (Unesp)-
Descrição: dc.descriptionDepartment of Support Production and Animal Health School of Veterinary Medicine of Araçatuba São Paulo State University (Unesp)-
Descrição: dc.descriptionDepartment of Preventive Veterinary Medicine and Animal Reproduction School of Agricultural and Veterinarian Sciences São Paulo State University (Unesp)-
Idioma: dc.languageen-
Relação: dc.relationMethods in Ecology and Evolution-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectadmixture-
Palavras-chave: dc.subjectchromosome painting-
Palavras-chave: dc.subjectpopulation structure-
Palavras-chave: dc.subjectsingle-nucleotide polymorphism-
Título: dc.titleUnsupervised detection of ancestry tracks with the GHap r package-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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