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ukbREST: efficient and streamlined data access for reproducible research in large biobanks
SUMMARY: 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 a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546122/ https://www.ncbi.nlm.nih.gov/pubmed/30395166 http://dx.doi.org/10.1093/bioinformatics/bty925 |
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author | Pividori, Milton Im, Hae Kyung |
author_facet | Pividori, Milton Im, Hae Kyung |
author_sort | Pividori, Milton |
collection | PubMed |
description | SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: 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: https://github.com/hakyimlab/ukbrest. |
format | Online Article Text |
id | pubmed-6546122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65461222019-06-13 ukbREST: efficient and streamlined data access for reproducible research in large biobanks Pividori, Milton Im, Hae Kyung Bioinformatics Applications Notes SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: 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: https://github.com/hakyimlab/ukbrest. Oxford University Press 2019-06-01 2018-11-05 /pmc/articles/PMC6546122/ /pubmed/30395166 http://dx.doi.org/10.1093/bioinformatics/bty925 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Pividori, Milton Im, Hae Kyung ukbREST: efficient and streamlined data access for reproducible research in large biobanks |
title | ukbREST: efficient and streamlined data access for reproducible research in large biobanks |
title_full | ukbREST: efficient and streamlined data access for reproducible research in large biobanks |
title_fullStr | ukbREST: efficient and streamlined data access for reproducible research in large biobanks |
title_full_unstemmed | ukbREST: efficient and streamlined data access for reproducible research in large biobanks |
title_short | ukbREST: efficient and streamlined data access for reproducible research in large biobanks |
title_sort | ukbrest: efficient and streamlined data access for reproducible research in large biobanks |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546122/ https://www.ncbi.nlm.nih.gov/pubmed/30395166 http://dx.doi.org/10.1093/bioinformatics/bty925 |
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