Kelliher Julia M, Xu Yan, Flynn Mark C, Babinski Michal, Canon Shane, Cavanna Eric, Clum Alicia, Corilo Yuri E, Fujimoto Grant, Giberson Cameron, Johnson Leah Y D, Li Kaitlyn J, Li Po-E, Li Valerie, Lo Chien-Chi, Lynch Wendi, Piehowski Paul, Prime Kaelan, Purvine Samuel, Rodriguez Francisca, Roux Simon, Shakya Migun, Smith Montana, Sarrafan Setareh, Cholia Shreyas, McCue Lee Ann, Mungall Chris, Hu Bin, Eloe-Fadrosh Emiley A, Chain Patrick S G
Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
Environmental Genomics & Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Comput Struct Biotechnol J. 2024 Sep 27;23:3575-3583. doi: 10.1016/j.csbj.2024.09.018. eCollection 2024 Dec.
Accessible and easy-to-use standardized bioinformatics workflows are necessary to advance microbiome research from observational studies to large-scale, data-driven approaches. Standardized multi-omics data enables comparative studies, data reuse, and applications of machine learning to model biological processes. To advance broad accessibility of standardized multi-omics bioinformatics workflows, the National Microbiome Data Collaborative (NMDC) has developed the Empowering the Development of Genomics Expertise (NMDC EDGE) resource, a user-friendly, open-source web application (https://nmdc-edge.org). Here, we describe the design and main functionality of the NMDC EDGE resource for processing metagenome, metatranscriptome, natural organic matter, and metaproteome data. The architecture relies on three main layers (web application, orchestration, and execution) to ensure flexibility and expansion to future workflows. The orchestration and execution layers leverage best practices in software containers and accommodate high-performance computing and cloud computing services. Further, we have adopted a robust user research process to collect feedback for continuous improvement of the resource. NMDC EDGE provides an accessible interface for researchers to process multi-omics microbiome data using production-quality workflows to facilitate improved data standardization and interoperability.
为了将微生物组研究从观察性研究推进到大规模、数据驱动的方法,需要有可访问且易于使用的标准化生物信息学工作流程。标准化的多组学数据能够实现比较研究、数据重用以及应用机器学习对生物过程进行建模。为了提高标准化多组学生物信息学工作流程的广泛可及性,国家微生物组数据协作组织(NMDC)开发了“增强基因组学专业知识发展”(NMDC EDGE)资源,这是一个用户友好的开源网络应用程序(https://nmdc-edge.org)。在此,我们描述了NMDC EDGE资源用于处理宏基因组、宏转录组、天然有机物和宏蛋白质组数据的设计和主要功能。该架构依赖于三个主要层次(网络应用程序、编排和执行),以确保灵活性并能扩展到未来的工作流程。编排层和执行层利用了软件容器中的最佳实践,并适应高性能计算和云计算服务。此外,我们采用了稳健的用户研究流程来收集反馈,以便对资源进行持续改进。NMDC EDGE为研究人员提供了一个可访问的界面,使他们能够使用高质量的生产工作流程来处理多组学微生物组数据,以促进提高数据标准化和互操作性。