Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets

Carla Márquez‐Luna(Broad Institute), Alkes L. Price(Broad Institute), Aaron Kleinman(23andMe (United States)), Babak Alipanahi(Google (United States)), J. Fah Sathirapongsasuti(Broad Institute), Nicholas A. Furlotte(23andMe (United States)), Joanna L. Mountain(Palo Alto Institute), Steven Gazal(University of Southern California), Adam Auton(23andMe (United States)), Po‐Ru Loh(Broad Institute), Sarah L. Elson, Nadia K. Litterman(Retrotope (United States)), David A. Hinds(23andMe (United States)), Michelle Agee(23andMe (United States)), Pierre Fontanillas(Royal Women's Hospital), Joyce Y. Tung(23andMe (United States)), Carrie A. M. Northover, Olga V. Sazonova(Ministry of Health of the Russian Federation), Catherine H. Wilson(The Gurdon Institute), Steven J. Pitts, Suyash Shringarpure(California Department of Parks and Recreation), Samuel S. Kim(Harvard University), Chao Tian, Katarzyna Bryc, Elizabeth S. Noblin, Karen E. Huber, Janie F. Shelton(23andMe (United States)), Robert K. Bell(Vancouver General Hospital), Jey C. McCreight(23andMe (United States)), Matthew H. McIntyre, Vladimir Vacic(23andMe (United States))
Nature Communications
October 18, 2021
Cited by 154


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