Computationally efficient whole-genome regression for quantitative and binary traits
Computationally efficient whole-genome regression for quantitative and binary traits
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Author / Creator
Mbatchou, Joelle , Barnard, Leland , Backman, Joshua , Marcketta, Anthony , Kosmicki, Jack A. , Ziyatdinov, Andrey , Benner, Christian , O’Dushlaine, Colm , Barber, Mathew , Boutkov, Boris , Habegger, Lukas , Ferreira, Manuel , Baras, Aris , Reid, Jeffrey , Abecasis, Goncalo , Maxwell, Evan and Marchini, Jonathan
Publisher
New York: Nature Publishing Group US
Journal title
Language
English
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Publication information
Publisher
New York: Nature Publishing Group US
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Scope and Contents
Contents
Genome-wide association analysis of cohorts with thousands of phenotypes is computationally expensive, particularly when accounting for sample relatedness or population structure. Here we present a novel machine-learning method called REGENIE for fitting a whole-genome regression model for quantitative and binary phenotypes that is substantially fa...
Alternative Titles
Full title
Computationally efficient whole-genome regression for quantitative and binary traits
Authors, Artists and Contributors
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Record Identifier
TN_cdi_proquest_miscellaneous_2531233864
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2531233864
Other Identifiers
ISSN
1061-4036
E-ISSN
1546-1718
DOI
10.1038/s41588-021-00870-7
