Author

George Tucker

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 2

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 2 Organism:human· 2 Approach:mixed model· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:fine-mapping· 1 Research Focus:genome assembly· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Alkes L Price· 2 shared Bonnie Berger· 2 shared Po-Ru LohiD· 2 shared Ben J Hayes· 1 shared Benjamin M Neale· 1 shared Bjarni J Vilhjalmsson· 1 shared Brendan K Bulik-SullivaniD· 1 shared Daniel I Chasman· 1 shared

Activity by Year

2015-2015 · peak 2/yr

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10 top collaborators · 35 mutual co-author links

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2 shared papersGenetics

Alkes L Price

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2 papers

Recent·Most cited

Two variance component model improves genetic prediction in family data sets

George Tucker, Po-Ru Loh, Iona M MacLeod, Ben J Hayes, Michael E Goddard, Bonnie Berger, Alkes L Price

This paper introduces a two variance component model that improves genetic prediction in family data by jointly modeling IBS sharing and pedigree structure, achieving higher prediction accuracy and correcting inflated test statistics.

bioRxiv · Jun 10, 2015 · PreprintGenetics

Efficient Bayesian mixed model analysis increases association power in large cohorts

Po-Ru Loh, George Tucker, Brendan K Bulik-Sullivan, Bjarni J Vilhjalmsson, Hilary K Finucane, Daniel I Chasman, Paul M Ridker, Benjamin M Neale, Bonnie Berger, Nick Patterson, Alkes L Price

BOLT-LMM improves genetic association power in large cohorts by using a Bayesian mixture prior to model non-infinitesimal genetic architectures more realistically.

Nature Genetics · Feb 2, 2015Peer-reviewedGenetics