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Building a Research-Quality Copy Number Variation Data Repository for Translational Research

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Heterogeneous Data Management, Polystores, and Analytics for Healthcare (DMAH 2018, Poly 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11470))

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Abstract

Copy number variation (CNV) has known associations with population diversities and disease conditions. However, research communities face great challenges in reusing the CNV data due to the heterogeneity of existing CNV data sources. The objective of the study is to design, develop and evaluate a scalable CNV data repository based on a proposed common data schema for facilitating research-quality CNV data integration and reuse. We created a proposal for a CNV common data schema through analyzing multiple existing CNV data sources. We designed a collection of the CNV quality metrics and demonstrated its usefulness using the CNV data from a study of ovarian cancer xenograft models. We implemented a CNV data repository using a MongoDB database backend and established the CNV genomic data services that enable reusing of the curated CNV data and answering CNV-relevant research questions. The critical issues and future plan for the system enhancement and community engagement were discussed.

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Acknowledgements

The study is supported in part by a NIH BD2KOnFHIR U01 project (U01 HG009450), a NCI U01 Project – caCDE-QA (U01 CA180940), the Mayo Clinic Specialized Program in Research Excellence (SPORE) grant P50 CA136393, R01 CA184502 from the National Institutes of Health, Minnesota Ovarian Cancer Alliance, and Ovarian Cancer Research Fund Alliance.

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Authors and Affiliations

  1. Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Chen Wang, Raymond M. Moore, Jared M. Evans, Xiaonan Hou, S. John Weroha & Guoqian Jiang

Authors
  1. Chen Wang
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  2. Raymond M. Moore
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  3. Jared M. Evans
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  4. Xiaonan Hou
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  5. S. John Weroha
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  6. Guoqian Jiang
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Corresponding author

Correspondence to Chen Wang .

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Editors and Affiliations

  1. Massachusetts Institute of Technology, Lexington, MA, USA

    Vijay Gadepally

  2. Intel Corporation, Hillsboro, OR, USA

    Timothy Mattson

  3. Massachusetts Institute of Technology, Cambridge, MA, USA

    Michael Stonebraker

  4. Stony Brook University, Stony Brook, NY, USA

    Fusheng Wang

  5. University of Washington, Seattle, WA, USA

    Gang Luo

  6. University of Brasília, Brasilia, Brazil

    George Teodoro

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Wang, C., Moore, R.M., Evans, J.M., Hou, X., John Weroha, S., Jiang, G. (2019). Building a Research-Quality Copy Number Variation Data Repository for Translational Research. In: Gadepally, V., Mattson, T., Stonebraker, M., Wang, F., Luo, G., Teodoro, G. (eds) Heterogeneous Data Management, Polystores, and Analytics for Healthcare. DMAH Poly 2018 2018. Lecture Notes in Computer Science(), vol 11470. Springer, Cham. https://doi.org/10.1007/978-3-030-14177-6_12

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  • DOI: https://doi.org/10.1007/978-3-030-14177-6_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14176-9

  • Online ISBN: 978-3-030-14177-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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