PhenoMeNal: processing and analysis of metabolomics data in the cloud
PhenoMeNal: processing and analysis of metabolomics data in the cloud
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DOI：
10.1093/gigascience/giy149
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发表时间：
2019-02-01
期刊：
影响因子：
9.2
通讯作者：
Steinbeck, Christoph
中科院分区：
文献类型：
--
作者：
Peters, Kristian;Bradbury, James;Steinbeck, Christoph
背景代谢组学是对多种小分子的综合研究，以深入了解生物体的新陈代谢。研究领域是动态的，应用范围涉及生物医学、生物技术和许多其他应用生物学领域。它的计算密集型特性推动了对开放数据格式、数据存储库和数据分析工具的需求。然而，快速的发展导致了独立的、有时不兼容的分析方法的马赛克，这些方法很难连接到有用的、完整的数据分析解决方案中。Finding现象(现象组和代谢组分析)是一个高级的完整解决方案，用于建立基础设施即服务(IaaS)，将面向工作流的、可互操作的代谢组学数据分析平台引入云中。现象无缝地集成了一系列现有的开源工具，这些工具通过项目的持续集成过程被测试和打包为Docker容器，并基于Kubernetes编排框架进行部署。它还在用户界面Galaxy、Jupyter、Luigi和Pachyderm中提供了许多标准化、自动化和发布的分析工作流。结论现象构成了可用于代谢组学的云电子基础设施中的关键解决方案。现象是一款独特的完整解决方案，可通过简单易用的Web界面设置云电子基础设施，该界面可扩展到任何定制的公共云和私有云环境。通过协调和自动化软件安装和配置，并通过现成的科学工作流用户界面，现象已成功地为科学家提供了工作流驱动的、可重复的和可共享的代谢组学数据分析平台，这些平台通过标准数据格式、代表性数据集、可重复性和互操作性进行了接口，并且已经过重复性和互操作性测试。现象学的弹性实现进一步允许基础设施轻松适应其他应用领域和组学研究领域。
Background Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools. However, the rapid progress has resulted in a mosaic of independent, and sometimes incompatible, analysis methods that are difficult to connect into a useful and complete data analysis solution.Findings PhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated, and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi, and Pachyderm.Conclusions PhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible, and shareable metabolomics data analysis platforms that are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adaptation of the infrastructure to other application areas and omics research domains.