University Hospital Georges Pompidou, HEGP, Department of Medical Informatics, AP-HP, INSERM, Centre de Recherche des Cordeliers, UMRS 1138, Université Sorbonne Paris Cité, University Paris-Descartes, Paris, France.
University Hospital Georges Pompidou, HEGP, Department of Biochemistry, Pharmacogenetics and Molecular Oncology, AP-HP, Paris, France, University Paris-Descartes.
Gigascience. 2017 Nov 1;6(11):1-9. doi: 10.1093/gigascience/gix099.
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.
下一代测序技术每天都被用于进行分子分析,以确定疾病的亚型(例如癌症),并协助选择最佳治疗方法。临床生物信息学处理测序仪生成的数据的操作,从生成到分析和解释。在临床环境中,可重复性和可追溯性是至关重要的问题。我们基于 Docker 容器技术和 Galaxy(流行的生物信息学分析支持开源软件)设计了一种方法。我们的解决方案简化了小型分析平台的部署,并简化了临床医生的流程。从技术角度来看,平台中嵌入的工具通过 Docker 映像进行隔离和版本控制。在 Galaxy 平台上,我们还引入了 AnalysisManager,这是一种允许生物学家一键分析的解决方案,并利用标准化的生物信息学应用程序编程接口。我们添加了一个 Shiny/R 交互式环境,以方便输出的可视化。该平台依赖于容器,并通过记录分析操作以及通过 ReGaTe 将工具的输入和输出与 EDAM 本体相关联来确保数据的可追溯性。源代码可在 Github 上免费获得,网址为 https://github.com/CARPEM/GalaxyDocker。