Observ-OM and Observ-TAB: Universal syntax solutions for the integration, search, and exchange of phenotype and genotype information

Authors

  • Tomasz Adamusiak,

    1. EU-GEN2PHEN
    2. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
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  • Helen Parkinson,

    1. EU-GEN2PHEN
    2. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
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    • These authors contributed equally to this work.

  • Juha Muilu,

    1. EU-GEN2PHEN
    2. Institute for Molecular Medicine Finland, Helsinki, Finland
    3. Biobanking and Molecular Resource Infrastructure (BBMRI) of Europe, BBMRI of the Netherlands, and BBMRI of Finland
    4. BioSHaRE-EU
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    • These authors contributed equally to this work.

  • Erik Roos,

    1. BioSHaRE-EU
    2. Genomics Coordination Center, Department of Genetics, University Medical Center Groningen and Groningen Bioinformatics Center, University of Groningen, Groningen, the Netherlands
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  • Kasper Joeri van der Velde,

    1. Genomics Coordination Center, Department of Genetics, University Medical Center Groningen and Groningen Bioinformatics Center, University of Groningen, Groningen, the Netherlands
    2. EU-PANACEA
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  • Gudmundur A. Thorisson,

    1. EU-GEN2PHEN
    2. Department of Genetics, University of Leicester, Leicester, United Kingdom
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  • Myles Byrne,

    1. EU-GEN2PHEN
    2. Institute for Molecular Medicine Finland, Helsinki, Finland
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  • Chao Pang,

    1. BioSHaRE-EU
    2. Genomics Coordination Center, Department of Genetics, University Medical Center Groningen and Groningen Bioinformatics Center, University of Groningen, Groningen, the Netherlands
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  • Sirisha Gollapudi,

    1. EU-GEN2PHEN
    2. Department of Genetics, University of Leicester, Leicester, United Kingdom
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  • Vincent Ferretti,

    1. BioSHaRE-EU
    2. Ontario Institute for Cancer Research, MaRS Center, Toronto, Ontario, Canada
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  • Hans Hillege,

    1. BioSHaRE-EU
    2. Department of Cardiology and Epidemiology, University Medical Center Groningen, Groningen, the Netherlands
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  • Anthony J. Brookes,

    1. EU-GEN2PHEN
    2. BioSHaRE-EU
    3. Department of Genetics, University of Leicester, Leicester, United Kingdom
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  • Morris A. Swertz

    Corresponding author
    1. EU-GEN2PHEN
    2. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
    3. Biobanking and Molecular Resource Infrastructure (BBMRI) of Europe, BBMRI of the Netherlands, and BBMRI of Finland
    4. BioSHaRE-EU
    5. Genomics Coordination Center, Department of Genetics, University Medical Center Groningen and Groningen Bioinformatics Center, University of Groningen, Groningen, the Netherlands
    6. EU-PANACEA
    7. Biobank TaskForce, Netherlands Bioinformatics Center, Nijmegen, the Netherlands
    • Genomics Coordination Center, Department of Genetics, HPC CB50, University Medical Center Groningen and Groningen Bioinformatics Center, University of Groningen, P.O. Box 30001, 9700 RB Groningen, the Netherlands.
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  • For the Deep Phenotyping Special Issue

Abstract

Genetic and epidemiological research increasingly employs large collections of phenotypic and molecular observation data from high quality human and model organism samples. Standardization efforts have produced a few simple formats for exchange of these various data, but a lightweight and convenient data representation scheme for all data modalities does not exist, hindering successful data integration, such as assignment of mouse models to orphan diseases and phenotypic clustering for pathways. We report a unified system to integrate and compare observation data across experimental projects, disease databases, and clinical biobanks. The core object model (Observ-OM) comprises only four basic concepts to represent any kind of observation: Targets, Features, Protocols (and their Applications), and Values. An easy-to-use file format (Observ-TAB) employs Excel to represent individual and aggregate data in straightforward spreadsheets. The systems have been tested successfully on human biobank, genome-wide association studies, quantitative trait loci, model organism, and patient registry data using the MOLGENIS platform to quickly setup custom data portals. Our system will dramatically lower the barrier for future data sharing and facilitate integrated search across panels and species. All models, formats, documentation, and software are available for free and open source (LGPLv3) at http://www.observ-om.org. Hum Mutat 33:867–873, 2012. © 2012 Wiley Periodicals, Inc.

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