Work

Mixed Model with Correction for Case-Control Ascertainment Increases Association Power

Year: 2015

Type: article

Source: The American Journal of Human Genetics

DOI: 10.1016/j.ajhg.2015.03.004

Authors: Tristan J. Hayeck, Noah A. Zaitlen, Po-Ru Loh, Bjarni Vilhjalmsson, Samuela Pollack, Alexander Gusev, Jian Yang, Guo-Bo Chen, Michael E. Goddard, Peter M. Visscher, Nick Patterson, Alkes L. Price

Institutions: Broad Institute, Harvard University, University of California, San Francisco, Massachusetts Institute of Technology, The University of Queensland, The University of Melbourne

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: Wellcome Trust, National Institutes of Health, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences

Awards: Richer Models of Asthma Risk: Bridging the Environment-Genetics Divide, Leveraging functional data to predict disease risk in multi-ethnic populations, Interdisciplinary training: Statistical Genetics/Genomics & Computational Biology, Fast and powerful extensions of mixed model methods for GWAS, Graduate Training in Biostatistics

OpenAlex ID: W2202191676

FWCI: 5.694

Cites: 46

Cited by: 68

Related to: 10