{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T17:54:38Z","timestamp":1785952478578,"version":"3.56.0"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"Supplement_2","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Sherlock cluster at Stanford University","award":["ECCB2022"],"award-info":[{"award-number":["ECCB2022"]}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01HG010140"],"award-info":[{"award-number":["R01HG010140"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,16]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Local ancestry inference (LAI) is the high resolution prediction of ancestry labels along a DNA sequence. LAI is important in the study of human history and migrations, and it is beginning to play a role in precision medicine applications including ancestry-adjusted genome-wide association studies (GWASs) and polygenic risk scores (PRSs). Existing LAI models do not generalize well between species, chromosomes or even ancestry groups, requiring re-training for each different setting. Furthermore, such methods can lack interpretability, which is an important element in each of these applications.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We present SALAI-Net, a portable statistical LAI method that can be applied on any set of species and ancestries (species-agnostic), requiring only haplotype data and no other biological parameters. Inspired by identity by descent methods, SALAI-Net estimates population labels for each segment of DNA by performing a reference matching approach, which leads to an interpretable and fast technique. We benchmark our models on whole-genome data of humans and we test these models\u2019 ability to generalize to dog breeds when trained on human data. SALAI-Net outperforms previous methods in terms of balanced accuracy, while generalizing between different settings, species and datasets. Moreover, it is up to two orders of magnitude faster and uses considerably less RAM memory than competing methods.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>We provide an open source implementation and links to publicly available data at github.com\/AI-sandbox\/SALAI-Net. Data is publicly available as follows: https:\/\/www.internationalgenome.org (1000 Genomes), https:\/\/www.simonsfoundation.org\/simons-genome-diversity-project (Simons Genome Diversity Project), https:\/\/www.sanger.ac.uk\/resources\/downloads\/human\/hapmap3.html (HapMap), ftp:\/\/ngs.sanger.ac.uk\/production\/hgdp\/hgdp_wgs.20190516 (Human Genome Diversity Project) and https:\/\/www.ncbi.nlm.nih.gov\/bioproject\/PRJNA448733 (Canid genomes).<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available from Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac464","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T09:17:32Z","timestamp":1663665452000},"page":"ii27-ii33","source":"Crossref","is-referenced-by-count":22,"title":["SALAI-Net: species-agnostic local ancestry inference network"],"prefix":"10.1093","volume":"38","author":[{"given":"Benet","family":"Oriol Sabat","sequence":"first","affiliation":[{"name":"Department of Signal Theory and Communications, Universitat Politecnica de Catalunya , Barcelona 08034, Spain"},{"name":"Department of Biomedical Data Science, Stanford Medical School"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Mas Montserrat","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Science, Stanford Medical School"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xavier","family":"Giro-i-Nieto","sequence":"additional","affiliation":[{"name":"Department of Signal Theory and Communications, Universitat Politecnica de Catalunya , Barcelona 08034, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander G","family":"Ioannidis","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Science, Stanford Medical School"},{"name":"Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,9,18]]},"reference":[{"key":"2023041408004057200_","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1002\/gepi.20378","article-title":"Relatedness mapping and tracts of relatedness for genome-wide data in the presence of linkage disequilibrium","volume":"33","author":"Albrechtsen","year":"2009","journal-title":"Genet. 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