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Nat Commun. 2017 Oct 27;8(1):1167. doi: 10.1038/s41467-017-00802-2.

PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies.

Author information

1
Institute for Biomedical Informatics, Departments of Genetics and Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
2
Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA, 17821, USA.
3
Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Eberly College of Science, The Pennsylvania State University, University Park, PA, 16802, USA.
4
Essentia Institute of Rural Health, Duluth, MN, 55805, USA.
5
Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA.
6
Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA, 17821, USA. mdritchie@geisinger.edu.
7
Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Eberly College of Science, The Pennsylvania State University, University Park, PA, 16802, USA. mdritchie@geisinger.edu.

Abstract

Genome-wide, imputed, sequence, and structural data are now available for exceedingly large sample sizes. The needs for data management, handling population structure and related samples, and performing associations have largely been met. However, the infrastructure to support analyses involving complexity beyond genome-wide association studies is not standardized or centralized. We provide the PLatform for the Analysis, Translation, and Organization of large-scale data (PLATO), a software tool equipped to handle multi-omic data for hundreds of thousands of samples to explore complexity using genetic interactions, environment-wide association studies and gene-environment interactions, phenome-wide association studies, as well as copy number and rare variant analyses. Using the data from the Marshfield Personalized Medicine Research Project, a site in the electronic Medical Records and Genomics Network, we apply each feature of PLATO to type 2 diabetes and demonstrate how PLATO can be used to uncover the complex etiology of common traits.

PMID:
29079728
PMCID:
PMC5660079
DOI:
10.1038/s41467-017-00802-2
[Indexed for MEDLINE]
Free PMC Article

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