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Inferring the ancestry of everyone

View ORCID ProfileJerome Kelleher, View ORCID ProfileYan Wong, View ORCID ProfilePatrick K. Albers, View ORCID ProfileAnthony W. Wohns, View ORCID ProfileGil McVean
doi: https://doi.org/10.1101/458067
Jerome Kelleher
1Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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Yan Wong
1Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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Patrick K. Albers
1Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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Anthony W. Wohns
1Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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Gil McVean
1Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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  • ORCID record for Gil McVean
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Abstract

A central problem in evolutionary biology is to infer the full genealogical history of a set of DNA sequences. This history contains rich information about the forces that have influenced a sexually reproducing species. However, existing methods are limited: the most accurate is unable to cope with more than a few dozen samples. With modern genetic data sets rapidly approaching millions of genomes, there is an urgent need for efficient inference methods to exploit such rich resources. We introduce an algorithm to infer whole-genome history which has comparable accuracy to the state-of-the-art but can process around four orders of magnitude more sequences. Additionally, our method results in an “evolutionary encoding” of the original sequence data, enabling efficient access to genealogies and calculation of genetic statistics over the data. We apply this technique to human data from the 1000 Genomes Project, Simons Genome Diversity Project and UK Biobank, showing that the genealogies we estimate are both rich in biological signal and efficient to process.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 01, 2018.
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Inferring the ancestry of everyone
Jerome Kelleher, Yan Wong, Patrick K. Albers, Anthony W. Wohns, Gil McVean
bioRxiv 458067; doi: https://doi.org/10.1101/458067
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Inferring the ancestry of everyone
Jerome Kelleher, Yan Wong, Patrick K. Albers, Anthony W. Wohns, Gil McVean
bioRxiv 458067; doi: https://doi.org/10.1101/458067

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