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The MRC IEU OpenGWAS data infrastructure

Ben Elsworth, Matthew Lyon, Tessa Alexander, Yi Liu, Peter Matthews, Jon Hallett, Phil Bates, Tom Palmer, Valeriia Haberland, George Davey Smith, Jie Zheng, Philip Haycock, Tom R Gaunt, View ORCID ProfileGibran Hemani
doi: https://doi.org/10.1101/2020.08.10.244293
Ben Elsworth
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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  • For correspondence: g.hemani@bristol.ac.uk
Matthew Lyon
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
2National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, UK
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Tessa Alexander
3Research IT, IT Services, University of Bristol, UK
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Yi Liu
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Peter Matthews
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Jon Hallett
3Research IT, IT Services, University of Bristol, UK
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Phil Bates
4Dept of Computer Science, University of Bristol, UK
5Oracle Corporation UK Ltd, Bristol, UK
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Tom Palmer
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Valeriia Haberland
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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George Davey Smith
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Jie Zheng
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Philip Haycock
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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Tom R Gaunt
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
2National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, UK
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  • For correspondence: g.hemani@bristol.ac.uk
Gibran Hemani
1MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
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  • ORCID record for Gibran Hemani
  • For correspondence: g.hemani@bristol.ac.uk
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Abstract

Data generated by genome-wide association studies (GWAS) are growing fast with the linkage of biobank samples to health records, and expanding capture of high-dimensional molecular phenotypes. However the utility of these efforts can only be fully realised if their complete results are collected from their heterogeneous sources and formats, harmonised and made programmatically accessible.

Here we present the OpenGWAS database, an open source, open access, scalable and high-performance cloud-based data infrastructure that imports and publishes complete GWAS summary datasets and metadata for the scientific community. Our import pipeline harmonises these datasets against dbSNP and the human genome reference sequence, generates summary reports and standardises the format of results and metadata. Users can access the data via a website, an application programming interface, R and Python packages, and also as downloadable files that can be rapidly queried in high performance computing environments.

OpenGWAS currently contains 126 billion genetic associations from 14,582 complete GWAS datasets representing a range of different human phenotypes and disease outcomes across different populations. We developed R and Python packages to serve as conduits between these GWAS data sources and a range of available analytical tools, enabling Mendelian randomization, genetic colocalisation analysis, fine mapping, genetic correlation and locus visualisation.

OpenGWAS is freely accessible at https://gwas.mrcieu.ac.uk, and has been designed to facilitate integration with third party analytical tools.

Competing Interest Statement

TRG, GH and GDS have received research funding from GlaxoSmithKline and Biogen for projects that use the MRC IEU OpenGWAS database. VH has previously been supported by funding from GlaxoSmithKline. Neither company had any input into or control over the contents of this manuscript. Oracle have provided cloud resources to host the OpenGWAS database.

Footnotes

  • https://gwas.mrcieu.ac.uk/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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The MRC IEU OpenGWAS data infrastructure
Ben Elsworth, Matthew Lyon, Tessa Alexander, Yi Liu, Peter Matthews, Jon Hallett, Phil Bates, Tom Palmer, Valeriia Haberland, George Davey Smith, Jie Zheng, Philip Haycock, Tom R Gaunt, Gibran Hemani
bioRxiv 2020.08.10.244293; doi: https://doi.org/10.1101/2020.08.10.244293
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The MRC IEU OpenGWAS data infrastructure
Ben Elsworth, Matthew Lyon, Tessa Alexander, Yi Liu, Peter Matthews, Jon Hallett, Phil Bates, Tom Palmer, Valeriia Haberland, George Davey Smith, Jie Zheng, Philip Haycock, Tom R Gaunt, Gibran Hemani
bioRxiv 2020.08.10.244293; doi: https://doi.org/10.1101/2020.08.10.244293

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