Mixed Model Association Testing is a statistical method that belongs to the class of association testing frameworks and is distinguished by its incorporation of both fixed and random effects to account for population structure and relatedness in quantitative trait analysis.
17
Publications
2.6K
Citations
113
Authors
59
Institutions
Publications per year
2017–2026
9
Variants
Mmat
Parents
Publications
17
Efficient Bayesian mixed-model analysis increases association power in large cohorts
Po‐Ru Loh, George Tucker, Brendan Bulik‐Sullivan et al. · Nature Genetics · 2015 · 1.8K citations · Full text
GWAS and fine-mapping of livability and six disease traits in Holstein cattle
Ellen Freebern, Daniel Jordan de Abreu Santos, Lingzhao Fang et al. · BMC Genomics · 2020 · 145 citations · Full text
1–5 of 17
Authors
113
- MJ
3
h-index
- BM
3
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- ZZ
2
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- SA
2
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- GR
2
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1–5 of 113
Institutions
59
Broad Institute
Cambridge, United States
5 h-index
18 publications
13.6K citations
Massachusetts General Hospital
Boston, United States
4 h-index
10 publications
1K citations
University of Michigan
Ann Arbor, United States
3 h-index
21 publications
3K citations
Norwegian University of Science and Technology
Trondheim, Norway
2 h-index
4 publications
594 citations
University of Chicago
Chicago, United States
2 h-index
5 publications
152 citations
University of California, Los Angeles
Los Angeles, United States
2 h-index
2 publications
41 citations
University of Pittsburgh
Pittsburgh, United States
2 h-index
4 publications
40 citations
The University of Texas Health Science Center at Houston
Houston, United States
2 h-index
5 publications
130 citations
1–8 of 59
Venues
- Genetic Epidemiology
2 publications · 40 citations
2
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- Nature Genetics
2 publications · 2K citations
2
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- Bioinformatics
2 publications · 23 citations
2
h-index
- BMC Genomics
2 publications · 236 citations
2
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- Human Molecular Genetics
1 publications · 28 citations
1
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1–5