Nature Communications (Jan 2021)
Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
- Ruowang Li,
- Rui Duan,
- Xinyuan Zhang,
- Thomas Lumley,
- Sarah Pendergrass,
- Christopher Bauer,
- Hakon Hakonarson,
- David S. Carrell,
- Jordan W. Smoller,
- Wei-Qi Wei,
- Robert Carroll,
- Digna R. Velez Edwards,
- Georgia Wiesner,
- Patrick Sleiman,
- Josh C. Denny,
- Jonathan D. Mosley,
- Marylyn D. Ritchie,
- Yong Chen,
- Jason H. Moore
Affiliations
- Ruowang Li
- Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania
- Rui Duan
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Xinyuan Zhang
- Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania
- Thomas Lumley
- Department of Statistics, University of Auckland
- Sarah Pendergrass
- Biomedical and Translational Informatics Institute
- Christopher Bauer
- Biomedical and Translational Informatics Institute
- Hakon Hakonarson
- Center for Applied Genomics, Children’s Hospital of Philadelphia
- David S. Carrell
- Kaiser Permanente Washington Health Research Institute
- Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital
- Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Centre
- Robert Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Centre
- Digna R. Velez Edwards
- Clinical and Translational Hereditary Cancer Program, Division of Genetic Medicine, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University
- Georgia Wiesner
- Clinical and Translational Hereditary Cancer Program, Division of Genetic Medicine, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University
- Patrick Sleiman
- Center for Applied Genomics, Children’s Hospital of Philadelphia
- Josh C. Denny
- Department of Biomedical Informatics, Vanderbilt University Medical Centre
- Jonathan D. Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Centre
- Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
- Yong Chen
- Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania
- Jason H. Moore
- Department of Biostatistics, Epidemiology & Informatics, University of Pennsylvania
- DOI
- https://doi.org/10.1038/s41467-020-20211-2
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 10
Abstract
Thus far, pleiotropy analysis using individual-level Electronic Health Records data has been limited to data from one site. Here, the authors introduce Sum-Share, a method designed to efficiently and losslessly integrate EHR and genetic data from multiple sites to perform pleiotropy analysis.
