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ukbtools: An R package to manage and query UK Biobank data

Author

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  • Ken B Hanscombe
  • Jonathan R I Coleman
  • Matthew Traylor
  • Cathryn M Lewis

Abstract

Introduction: The UK Biobank (UKB) is a resource that includes detailed health-related data on about 500,000 individuals and is available to the research community. However, several obstacles limit immediate analysis of the data: data files vary in format, may be very large, and have numerical codes for column names. Results: ukbtools removes all the upfront data wrangling required to get a single dataset for statistical analysis. All associated data files are merged into a single dataset with descriptive column names. The package also provides tools to assist in quality control by exploring the primary demographics of subsets of participants; query of disease diagnoses for one or more individuals, and estimating disease frequency relative to a reference variable; and to retrieve genetic metadata. Conclusion: Having a dataset with meaningful variable names, a set of UKB-specific exploratory data analysis tools, disease query functions, and a set of helper functions to explore and write genetic metadata to file, will rapidly enable UKB users to undertake their research.

Suggested Citation

  • Ken B Hanscombe & Jonathan R I Coleman & Matthew Traylor & Cathryn M Lewis, 2019. "ukbtools: An R package to manage and query UK Biobank data," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-6, May.
    • Handle: RePEc:plo:pone00:0214311
    DOI: 10.1371/journal.pone.0214311
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    References listed on IDEAS

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    1. Clare Bycroft & Colin Freeman & Desislava Petkova & Gavin Band & Lloyd T. Elliott & Kevin Sharp & Allan Motyer & Damjan Vukcevic & Olivier Delaneau & Jared O’Connell & Adrian Cortes & Samantha Welsh &, 2018. "The UK Biobank resource with deep phenotyping and genomic data," Nature, Nature, vol. 562(7726), pages 203-209, October.
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    Cited by:

    1. Clark, Stephen & Birkin, Mark & Lomax, Nik & Morris, Michelle, 2020. "Developing a whole systems obesity classification for the UK Biobank Cohort," OSF Preprints 7nqgd, Center for Open Science.
    2. Daniel E. Vosberg & Igor Jurisica & Zdenka Pausova & Tomáš Paus, 2024. "Intrauterine growth and the tangential expansion of the human cerebral cortex in times of food scarcity and abundance," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    3. Remo Monti & Pia Rautenstrauch & Mahsa Ghanbari & Alva Rani James & Matthias Kirchler & Uwe Ohler & Stefan Konigorski & Christoph Lippert, 2022. "Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes," Nature Communications, Nature, vol. 13(1), pages 1-16, December.

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