Journal
SCIENCE
Volume 375, Issue 6583, Pages 836-+Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.abi8264
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Funding
- Wellcome Trust [203141/Z/16/Z, 100956/Z/13/Z]
- Li Ka Shing Foundation
- Robertson Foundation
- Rhodes Trust
- NIH (NIGMS) [GM100233]
- Paul Allen Foundation
- John Templeton Foundation [61220]
- Howard Hughes Medical Institute
- NIHR Oxford BRC
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The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. Although the problem of characterizing ancestral relationships from genomic variation remains unsolved, nonparametric methods have been used successfully to infer a unified genealogy of modern and ancient humans, identify descendants of ancient samples, and estimate geographical location of ancestors.
The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.
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