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Efficient Bayesian mixed model analysis increases association power in large cohorts
Po-Ru Loh, George Tucker, Brendan K Bulik-Sullivan, Bjarni J Vilhjálmsson, Hilary K Finucane, Daniel I Chasman, Paul M Ridker, Benjamin M Neale, Bonnie Berger, Nick Patterson, Alkes L Price
doi: https://doi.org/10.1101/007799
Po-Ru Loh
1Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.
2Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
George Tucker
1Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.
3Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
4Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts, USA.
Brendan K Bulik-Sullivan
2Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
5Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
Bjarni J Vilhjálmsson
1Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.
2Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
Hilary K Finucane
3Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Daniel I Chasman
6Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA.
Paul M Ridker
6Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA.
Benjamin M Neale
2Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
5Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
Bonnie Berger
3Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
4Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts, USA.
Nick Patterson
2Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
Alkes L Price
1Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.
2Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
7Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.
Article usage
Posted August 09, 2014.
Efficient Bayesian mixed model analysis increases association power in large cohorts
Po-Ru Loh, George Tucker, Brendan K Bulik-Sullivan, Bjarni J Vilhjálmsson, Hilary K Finucane, Daniel I Chasman, Paul M Ridker, Benjamin M Neale, Bonnie Berger, Nick Patterson, Alkes L Price
bioRxiv 007799; doi: https://doi.org/10.1101/007799
Efficient Bayesian mixed model analysis increases association power in large cohorts
Po-Ru Loh, George Tucker, Brendan K Bulik-Sullivan, Bjarni J Vilhjálmsson, Hilary K Finucane, Daniel I Chasman, Paul M Ridker, Benjamin M Neale, Bonnie Berger, Nick Patterson, Alkes L Price
bioRxiv 007799; doi: https://doi.org/10.1101/007799
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