ukbtools: An R package to manage and query UK Biobank data
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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.
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They removed an additional 24,116 (5.1%) sequences by choosing a subset with no pair having a kinship coefficient exceeding 0.1769.
“We used the ukb_gen_samples_to_remove() function from the R package ukbtools v.0.11.3 (ref. 71) to choose a subset of individuals within which no pair had a kinship coefficient exceeding 0.1769, to exclude predicted first-degree relatives.”
From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [71]
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- [2]Chang C C, Chow C C, Tellier L C A M, Vattikuti S, Purcell S M, Lee J J. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience. 2015: 4 Available from: www.cog-genomics.org/plink/1.9/ PMC4342193 25722852
- [3]Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018; 562: 203– 209 10.1038/s41586-018-0579-z 30305743 PMC6786975 · DOI · Paper page
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Rare variant associations with plasma protein levels in the UK Biobank
Dhindsa, R. S., Burren, O. S., Sun, B. B., Prins, B. P., Matelska, D., Wheeler, E., Mitchell, J., Oerton, E., Hristova, V. A., Smith, K. R., et al. (2023) · Nature · doi:10.1038/s41586-023-06547-x · Cited by 193 · see citing works
- Authors
- Hanscombe, K. B., Coleman, J. R. I., Traylor, M., & Lewis, C. M.
- Affiliations
- King's College London (GB)
- University of Cambridge (GB)
- Corresponding author
- Hanscombe, Ken B.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2019-05-31
- Volume
- 14
- Issue
- 5
- Pages
- e0214311
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC6544205
- OpenAlex
- W2951438521
- Cited by
- 54
- References
- 0
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 4 · 2023: 12 · 2022: 9 · 2021: 8 · 2020: 5 · 2019: 1
- FWCI
- 3.42
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (acceptedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- South London and Maudsley NHS Foundation Trust
- NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
- National Institute for Health and Care Research
- King's College London
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Physical Sciences › Computer Science › Artificial Intelligence › Data Analysis with R
- Keywords
- UK Biobank, R package, data wrangling, data merging, quality control, participant demographics
- MeSH terms
- Metadata, Data Analysis, Database Management Systems, Disease, United Kingdom, Humans, Information Storage and Retrieval, Electronic Health Records, Datasets as Topic
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