计算代谢组学工作流程中FAIR原则的实施——一个案例研究

Implementation of FAIR Practices in Computational Metabolomics Workflows-A Case Study.

作者信息

Zulfiqar Mahnoor, Crusoe Michael R, König-Ries Birgitta, Steinbeck Christoph, Peters Kristian, Gadelha Luiz

机构信息

Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, 07743 Jena, Germany.

Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany.

出版信息

Metabolites. 2024 Feb 10;14(2):118. doi: 10.3390/metabo14020118.

DOI:10.3390/metabo14020118

PMID:38393009

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10891576/

Abstract

Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for metabolomics workflows using the Metabolome Annotation Workflow (MAW) as a case study. MAW is specified using the Common Workflow Language (CWL), allowing for the subsequent execution of the workflow on different workflow engines. MAW is registered using a CWL description on WorkflowHub. During the submission process on WorkflowHub, a CWL description is used for packaging MAW using the Workflow RO-Crate profile, which includes metadata in Bioschemas. Researchers can use this narrative discussion as a guideline to commence using FAIR practices for their bioinformatics or cheminformatics workflows while incorporating necessary amendments specific to their research area.

摘要

科学工作流程通过整合按特定顺序执行的各种软件和工具，促进了数据分析任务的自动化。为了在工作流程中实现透明度和可重用性，实施FAIR原则至关重要。在这里，我们以代谢组学注释工作流程（MAW）为例，描述我们在代谢组学工作流程中实施FAIR原则的经验。MAW使用通用工作流语言（CWL）进行指定，允许随后在不同的工作流引擎上执行该工作流程。MAW使用CWL描述在WorkflowHub上注册。在WorkflowHub上的提交过程中，使用CWL描述通过工作流RO-Crate配置文件对MAW进行打包，该配置文件包括生物模式中的元数据。研究人员可以将此叙述性讨论作为指南，开始在其生物信息学或化学信息学工作流程中使用FAIR实践，同时纳入其研究领域特有的必要修改。