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

Abstract : 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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https://www.hal.inserm.fr/inserm-01958151
Contributor : Bastien Rance <>
Submitted on : Monday, December 17, 2018 - 5:17:42 PM
Last modification on : Friday, December 13, 2019 - 12:04:02 PM

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William Digan, Hector Countouris, Marc Barritault, David Baudoin, Pierre Laurent-Puig, et al.. An architecture for genomics analysis in a clinical setting using Galaxy and Docker. GigaScience, BioMed Central, 2017, 6 (11), ⟨10.1093/gigascience/gix099⟩. ⟨inserm-01958151⟩

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