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iRODS metadata management for a cancer genome analysis workflow
BACKGROUND: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. RESULTS: We desc...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334444/ https://www.ncbi.nlm.nih.gov/pubmed/30646845 http://dx.doi.org/10.1186/s12859-018-2576-5 |
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author | Nieroda, Lech Maas, Lukas Thiebes, Scott Lang, Ulrich Sunyaev, Ali Achter, Viktor Peifer, Martin |
author_facet | Nieroda, Lech Maas, Lukas Thiebes, Scott Lang, Ulrich Sunyaev, Ali Achter, Viktor Peifer, Martin |
author_sort | Nieroda, Lech |
collection | PubMed |
description | BACKGROUND: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. RESULTS: We describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information. CONCLUSIONS: Integrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments. |
format | Online Article Text |
id | pubmed-6334444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63344442019-01-23 iRODS metadata management for a cancer genome analysis workflow Nieroda, Lech Maas, Lukas Thiebes, Scott Lang, Ulrich Sunyaev, Ali Achter, Viktor Peifer, Martin BMC Bioinformatics Methodology Article BACKGROUND: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. RESULTS: We describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information. CONCLUSIONS: Integrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments. BioMed Central 2019-01-15 /pmc/articles/PMC6334444/ /pubmed/30646845 http://dx.doi.org/10.1186/s12859-018-2576-5 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Nieroda, Lech Maas, Lukas Thiebes, Scott Lang, Ulrich Sunyaev, Ali Achter, Viktor Peifer, Martin iRODS metadata management for a cancer genome analysis workflow |
title | iRODS metadata management for a cancer genome analysis workflow |
title_full | iRODS metadata management for a cancer genome analysis workflow |
title_fullStr | iRODS metadata management for a cancer genome analysis workflow |
title_full_unstemmed | iRODS metadata management for a cancer genome analysis workflow |
title_short | iRODS metadata management for a cancer genome analysis workflow |
title_sort | irods metadata management for a cancer genome analysis workflow |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334444/ https://www.ncbi.nlm.nih.gov/pubmed/30646845 http://dx.doi.org/10.1186/s12859-018-2576-5 |
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