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  4. BugBuster: a novel automatic and reproducible workflow for metagenomic data analysis
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BugBuster: a novel automatic and reproducible workflow for metagenomic data analysis

Journal
Bioinformatics Advances
ISSN
2635-0041
Date Issued
2024-12-26
Author(s)
Francisco Fuentes-Santander
Carolina Curiqueo
PEREZ ARAOS, RODRIGO ALEJANDRO  
Facultad de Medicina ClĂ­nica Alemana Universidad del Desarrollo  
Juan A Ugalde
Type
journal-article
DOI
10.1093/bioadv/vbaf152
URL
https://hdl.handle.net/123456789/11363
Abstract
<jats:title>Abstract</jats:title>
<jats:sec>
<jats:title>Summary</jats:title>
<jats:p>Metagenomic sequencing generates massive datasets that capture the complete genetic content of a sample, enabling detailed characterization of microbial communities. Yet the software and processes necessary to transform raw data into biologically meaningful results have become increasingly complex, limiting accessibility for researchers without specialist expertise. In this work, we present a novel modular a reproducible workflow developed to facilitate the analysis of metagenomic data. BugBuster is a fully containerized, modular, and reproducible workflow implemented in Nextflow. The pipeline streamlines analysis at level of reads, contigs, and metagenome-assembled genomes, offering dedicated modules for taxonomic profiling and resistome characterization. Thanks to the use of containers, BugBuster can be deployed with minimal configuration on workstations, high-performance clusters, or cloud platforms. Together, these features allow the robust, scalable, and reproducible analysis of metagenomic datasets.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Availability and implementation</jats:title>
<jats:p>BugBuster was written in Nextflow-DSL2. The program applications, user manual, example data and code are freely available at https://github.com/gene2dis/BugBuster.</jats:p>
</jats:sec>
Cite this document
Fuentes-Santander, F., Curiqueo, C., Araos, R., & Ugalde, J. A. (2024). BugBuster: A novel automatic and reproducible workflow for metagenomic data analysis. Bioinformatics Advances, 5(1), vbaf152. https://doi.org/10.1093/bioadv/vbaf152
Dataset(s)
Dataset - BugBuster: a novel automatic and reproducible workflow for metagenomic data analysis  
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