ArticleNature communications2025
Tracing human genetic histories and natural selection with precise local ancestry inference.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Scalable high resolution ancestry deconvolution for genomic data.Nature communications · 2026Article
- A transparent and generalizable deep-learning framework for genomic ancestry prediction.American journal of human genetics · 2026Article
- Strategies in Global Ancestry and Local Ancestry Inference.Current protocols · 2026Article
- Tracing the evolutionary histories of ultra-rare variants using variational dating of large ancestral recombination graphs.bioRxiv : the preprint server for biology · 2026Article
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Authors and funding
16 authors.
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Abstract
Local ancestry inference is crucial for unraveling demographic histories, discovering selection signals, and including admixed individuals in genomic studies for improved equity and portability. To date, the precision and resolution of local ancestry inference were limited by technical and dataset issues. To address them, we present Orchestra, a model we train on over 10,000 single-origin individuals from 35 worldwide populations that demonstrates superior accuracy in benchmarking analyzes. We employ Orchestra to shed light on the demographic history of Latin Americans, finding trace ancestries supported by historical records. We then deploy it to offer insight on the debated Ashkenazi Jewish origins, highlighting their South European heritage. Finally, Orchestra enables us to map selection signatures, identifying trace Scandinavian ancestry in British samples and unveiling an immune-rich region linked to respiratory infections passed down from the Viking conquests. Our work significantly advances the field of local ancestry inference, highlighting its use in admixed populations.
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