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An architecture for genomics analysis in a clinical setting using Galaxy and Docker

Next-generation sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g., in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation t...

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Detalles Bibliográficos
Autores principales: Digan, W, Countouris, H, Barritault, M, Baudoin, D, Laurent-Puig, P, Blons, H, Burgun, A, Rance, B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691353/
https://www.ncbi.nlm.nih.gov/pubmed/29048555
http://dx.doi.org/10.1093/gigascience/gix099
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author Digan, W
Countouris, H
Barritault, M
Baudoin, D
Laurent-Puig, P
Blons, H
Burgun, A
Rance, B
author_facet Digan, W
Countouris, H
Barritault, M
Baudoin, D
Laurent-Puig, P
Blons, H
Burgun, A
Rance, B
author_sort Digan, W
collection PubMed
description Next-generation sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g., in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation to the analysis and interpretation. Reproducibility and traceability are crucial issues in a clinical setting. We have designed an approach based on Docker container technology and Galaxy, the popular bioinformatics analysis support open-source software. Our solution simplifies the deployment of a small-size analytical platform and simplifies the process for the clinician. From the technical point of view, the tools embedded in the platform are isolated and versioned through Docker images. Along the Galaxy platform, we also introduce the AnalysisManager, a solution that allows single-click analysis for biologists and leverages standardized bioinformatics application programming interfaces. We added a Shiny/R interactive environment to ease the visualization of the outputs. The platform relies on containers and ensures the data traceability by recording analytical actions and by associating inputs and outputs of the tools to EDAM ontology through ReGaTe. The source code is freely available on Github at https://github.com/CARPEM/GalaxyDocker.
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spelling pubmed-56913532017-12-11 An architecture for genomics analysis in a clinical setting using Galaxy and Docker Digan, W Countouris, H Barritault, M Baudoin, D Laurent-Puig, P Blons, H Burgun, A Rance, B Gigascience Technical Note Next-generation sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g., in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation to the analysis and interpretation. Reproducibility and traceability are crucial issues in a clinical setting. We have designed an approach based on Docker container technology and Galaxy, the popular bioinformatics analysis support open-source software. Our solution simplifies the deployment of a small-size analytical platform and simplifies the process for the clinician. From the technical point of view, the tools embedded in the platform are isolated and versioned through Docker images. Along the Galaxy platform, we also introduce the AnalysisManager, a solution that allows single-click analysis for biologists and leverages standardized bioinformatics application programming interfaces. We added a Shiny/R interactive environment to ease the visualization of the outputs. The platform relies on containers and ensures the data traceability by recording analytical actions and by associating inputs and outputs of the tools to EDAM ontology through ReGaTe. The source code is freely available on Github at https://github.com/CARPEM/GalaxyDocker. Oxford University Press 2017-10-18 /pmc/articles/PMC5691353/ /pubmed/29048555 http://dx.doi.org/10.1093/gigascience/gix099 Text en © The Author 2017. 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 Technical Note
Digan, W
Countouris, H
Barritault, M
Baudoin, D
Laurent-Puig, P
Blons, H
Burgun, A
Rance, B
An architecture for genomics analysis in a clinical setting using Galaxy and Docker
title An architecture for genomics analysis in a clinical setting using Galaxy and Docker
title_full An architecture for genomics analysis in a clinical setting using Galaxy and Docker
title_fullStr An architecture for genomics analysis in a clinical setting using Galaxy and Docker
title_full_unstemmed An architecture for genomics analysis in a clinical setting using Galaxy and Docker
title_short An architecture for genomics analysis in a clinical setting using Galaxy and Docker
title_sort architecture for genomics analysis in a clinical setting using galaxy and docker
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691353/
https://www.ncbi.nlm.nih.gov/pubmed/29048555
http://dx.doi.org/10.1093/gigascience/gix099
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