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

Molly A. Hall; John Wallace; Anastasia Lucas; Dokyoon Kim; Anna O. Basile; Shefali S. Verma; Cathy A. McCarty; Murray H. Brilliant; Peggy L. Peissig; Terrie E. Kitchner; Anurag Verma; Sarah A. Pendergrass; Scott M. Dudek; Jason H. Moore; Marylyn D. Ritchie

doi:10.1038/s41467-017-00802-2

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

Molly A. Hall, John Wallace, Anastasia Lucas, Dokyoon Kim, Anna O. Basile, Shefali S. Verma, Cathy A. McCarty, Murray H. Brilliant, Peggy L. Peissig, Terrie E. Kitchner, Anurag Verma, Sarah A. Pendergrass, Scott M. Dudek, Jason H. Moore, Marylyn D. Ritchie

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

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.

Original language	English (US)
Article number	1167
Journal	Nature communications
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41467-017-00802-2
State	Published - Dec 1 2017

All Science Journal Classification (ASJC) codes

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-017-00802-2

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Hall, M. A., Wallace, J., Lucas, A., Kim, D., Basile, A. O., Verma, S. S., McCarty, C. A., Brilliant, M. H., Peissig, P. L., Kitchner, T. E., Verma, A., Pendergrass, S. A., Dudek, S. M., Moore, J. H., & Ritchie, M. D. (2017). PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies. Nature communications, 8(1), Article 1167. https://doi.org/10.1038/s41467-017-00802-2

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title = "PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies",

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.",

author = "Hall, {Molly A.} and John Wallace and Anastasia Lucas and Dokyoon Kim and Basile, {Anna O.} and Verma, {Shefali S.} and McCarty, {Cathy A.} and Brilliant, {Murray H.} and Peissig, {Peggy L.} and Kitchner, {Terrie E.} and Anurag Verma and Pendergrass, {Sarah A.} and Dudek, {Scott M.} and Moore, {Jason H.} and Ritchie, {Marylyn D.}",

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Hall, MA, Wallace, J, Lucas, A, Kim, D, Basile, AO, Verma, SS, McCarty, CA, Brilliant, MH, Peissig, PL, Kitchner, TE, Verma, A, Pendergrass, SA, Dudek, SM, Moore, JH & Ritchie, MD 2017, 'PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies', Nature communications, vol. 8, no. 1, 1167. https://doi.org/10.1038/s41467-017-00802-2

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AU - Verma, Anurag

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AU - Moore, Jason H.

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

Abstract

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UN SDGs

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