Camp : a modular metagenomics analysis system for integrated multistep data exploration
(2026) In NAR Genomics and Bioinformatics 8(1).- Abstract
Computational analysis of large-scale metagenomics sequencing datasets provides valuable isolate-level taxonomic and functional insights from complex microbial communities. However, the ever-expanding ecosystem of metagenomics-specific methods and file formats makes designing scalable workflows and seamlessly exploring output data increasingly challenging. Although one-click bioinformatics pipelines can help organize these tools into workflows, they face compatibility and maintainability challenges that can prevent replication. To address the gap in easily extensible yet robustly distributable metagenomics workflows, we have developed the Core Analysis Modular Pipeline (CAMP), a module-based metagenomics analysis system written in... (More)
Computational analysis of large-scale metagenomics sequencing datasets provides valuable isolate-level taxonomic and functional insights from complex microbial communities. However, the ever-expanding ecosystem of metagenomics-specific methods and file formats makes designing scalable workflows and seamlessly exploring output data increasingly challenging. Although one-click bioinformatics pipelines can help organize these tools into workflows, they face compatibility and maintainability challenges that can prevent replication. To address the gap in easily extensible yet robustly distributable metagenomics workflows, we have developed the Core Analysis Modular Pipeline (CAMP), a module-based metagenomics analysis system written in Snakemake, with a standardized module and directory architecture. Each module can run independently or in sequence to produce target data formats (e.g. short-read preprocessing alone or followed by de novo assembly), and provides output summary statistics reports and Jupyter notebook-based visualizations. We applied CAMP to a set of 10 metagenomics samples, demonstrating how a modular analysis system with built-in data visualization facilitates rich seamless communication between outputs from different analytical purposes. The CAMP ecosystem (module template and analysis modules) can be found at https://github.com/Meta-CAMP.
(Less)
- author
- author collaboration
- organization
- publishing date
- 2026-03
- type
- Contribution to journal
- publication status
- published
- keywords
- Metagenomics/methods, Software, Workflow, Computational Biology/methods, Microbiota
- in
- NAR Genomics and Bioinformatics
- volume
- 8
- issue
- 1
- article number
- lqaf172
- publisher
- Oxford University Press
- external identifiers
-
- pmid:41551931
- ISSN
- 2631-9268
- DOI
- 10.1093/nargab/lqaf172
- language
- English
- LU publication?
- yes
- additional info
- © The Author(s) 2026. Published by Oxford University Press.
- id
- 6d69033c-d34a-42f5-bfcc-d111a69988cd
- date added to LUP
- 2026-01-22 11:09:27
- date last changed
- 2026-01-22 11:09:27
@article{6d69033c-d34a-42f5-bfcc-d111a69988cd,
abstract = {{<p>Computational analysis of large-scale metagenomics sequencing datasets provides valuable isolate-level taxonomic and functional insights from complex microbial communities. However, the ever-expanding ecosystem of metagenomics-specific methods and file formats makes designing scalable workflows and seamlessly exploring output data increasingly challenging. Although one-click bioinformatics pipelines can help organize these tools into workflows, they face compatibility and maintainability challenges that can prevent replication. To address the gap in easily extensible yet robustly distributable metagenomics workflows, we have developed the Core Analysis Modular Pipeline (CAMP), a module-based metagenomics analysis system written in Snakemake, with a standardized module and directory architecture. Each module can run independently or in sequence to produce target data formats (e.g. short-read preprocessing alone or followed by de novo assembly), and provides output summary statistics reports and Jupyter notebook-based visualizations. We applied CAMP to a set of 10 metagenomics samples, demonstrating how a modular analysis system with built-in data visualization facilitates rich seamless communication between outputs from different analytical purposes. The CAMP ecosystem (module template and analysis modules) can be found at https://github.com/Meta-CAMP.</p>}},
author = {{Mak, Lauren and Tierney, Braden and Wei, Wei and Ronkowski, Cynthia and Toscan, Rodolfo Brizola and Turhan, Berk and Toomey, Michael and Andrade-Martínez, Juan Sebastian and Fu, Chenlian and Lucaci, Alexander G and Solano, Arthur Henrique Barrios and Setubal, João Carlos and Henriksen, James R and Zimmerman, Sam and Kopbayeva, Malika and Noyvert, Anna and Iwan, Zana and Kar, Shraman and Nakazawa, Nikita and Meleshko, Dmitry and Horyslavets, Dmytro and Kantsypa, Valeriia and Frolova, Alina and Kahles, Andre and Danko, David and Elhaik, Eran and Labaj, Pawel and Mangul, Serghei and Mason, Christopher E and Hajirasouliha, Iman}},
issn = {{2631-9268}},
keywords = {{Metagenomics/methods; Software; Workflow; Computational Biology/methods; Microbiota}},
language = {{eng}},
number = {{1}},
publisher = {{Oxford University Press}},
series = {{NAR Genomics and Bioinformatics}},
title = {{Camp : a modular metagenomics analysis system for integrated multistep data exploration}},
url = {{http://dx.doi.org/10.1093/nargab/lqaf172}},
doi = {{10.1093/nargab/lqaf172}},
volume = {{8}},
year = {{2026}},
}
