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Bioinformatics. 2018 Nov 5. doi: 10.1093/bioinformatics/bty925. [Epub ahead of print]

ukbREST: efficient and streamlined data access for reproducible research in large biobanks.

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Section of Genetic Medicine, Department of Medicine, The University of Chicago, IL, USA.
Center for Translational Data Science, The University of Chicago, IL, USA.



Large biobanks, such as UK Biobank with half a million participants, are changing the scale and availability of genotypic and phenotypic data for researchers to ask fundamental questions about the biology of health and disease. The breadth of the UK Biobank data is enabling discoveries at an unprecedented pace. However, this size and complexity pose new challenges to investigators who need to keep the accruing data up to date, comply with potential consent changes, and efficiently and reproducibly extract subsets of the data to answer specific scientific questions. Here we propose a tool called ukbREST designed for the UK Biobank study (easily extensible to other biobanks), which allows authorized users to efficiently retrieve phenotypic and genetic data. It exposes a REST API that makes data highly accessible inside a private and secure network, allowing the data specification in a human readable text format easily shareable with other researchers. These characteristics make ukbREST an important tool to make biobank's valuable data more readily accessible to the research community and facilitate reproducibility of the analysis, a key aspect of science.


It is implemented in Python using the Flask-RESTful framework for the API, and it is under the MIT license. It works with PostgreSQL and a Docker image is available for easy deployment. The source code and documentation is available in Github:

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