Standardized and accessible multi-omics bioinformatics workflows through the NMDC EDGE resource
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.
Authors
- Michal Babinski (ORCID: https://orcid.org/0000-0003-2871-7807)
- Chris Mungall (ORCID: https://orcid.org/0000-0002-6601-2165)
- Cameron M. Giberson (ORCID: https://orcid.org/0000-0001-8536-8573)
- Patrick Chain (ORCID: https://orcid.org/0000-0003-3949-3634)
- Paul Piehowski (ORCID: https://orcid.org/0000-0001-5108-2227)
- Simon Roux (ORCID: https://orcid.org/0000-0002-5831-5895)
- Julia M. Kelliher (ORCID: https://orcid.org/0000-0003-4100-9119)
- Po‐E Li (ORCID: https://orcid.org/0000-0003-4290-1993)
- Kongning Li
- Mark Flynn (ORCID: https://orcid.org/0000-0002-6162-9510)
- Samuel Purvine (ORCID: https://orcid.org/0000-0002-2257-2400)
- Montana Smith (ORCID: https://orcid.org/0000-0002-8683-0050)
- Alicia Clum (ORCID: https://orcid.org/0000-0002-5004-3362)
- L. Johnson (ORCID: https://orcid.org/0000-0001-5896-0344)
- Vincent Cheng-Sheng Li
- Bin Hu (ORCID: https://orcid.org/0000-0002-0278-8466)
- Grant M. Fujimoto (ORCID: https://orcid.org/0000-0002-9522-8256)
- Lee Ann McCue (ORCID: https://orcid.org/0000-0003-4456-517X)
- Shane Canon (ORCID: https://orcid.org/0000-0002-8440-738X)
- Emiley A. Eloe‐Fadrosh (ORCID: https://orcid.org/0000-0002-8162-1276)
- Yuri Corilo (ORCID: https://orcid.org/0000-0002-1368-8217)
- Shreyas Cholia (ORCID: https://orcid.org/0000-0002-4775-8201)
- Wendi Lynch
- Chien‐Chi Lo (ORCID: https://orcid.org/0000-0003-3470-1078)
- Francisca E. Rodriguez (ORCID: https://orcid.org/0000-0001-5778-0288)
- Setareh Sarrafan (ORCID: https://orcid.org/0000-0001-6870-7289)
- Migun Shakya (ORCID: https://orcid.org/0000-0003-3876-691X)
- Eric Cavanna
- Yan Xu (ORCID: https://orcid.org/0009-0005-8274-8681)
- Kaelan Prime
Institutions
- Los Alamos National Laboratory (US)
- Pacific Northwest National Laboratory (US)
- Lawrence Berkeley National Laboratory (US)
Publication Details
- Journal
- Computational and Structural Biotechnology Journal
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1016/j.csbj.2024.09.018
- Citations
- 13
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 13.66
Funders
- National Science Foundation
- U.S. Department of Energy
- San Diego Supercomputer Center
- Office of Science
- Office of Advanced Cyberinfrastructure
- Biological and Environmental Research
- Lawrence Berkeley National Laboratory
- Los Alamos National Laboratory
- Pacific Northwest National Laboratory