Hecatomb: an integrated software platform for viral metagenomics

• Published in: Gigascience Vol. 13
• Main Authors: Roach, Michael J, Beecroft, Sarah J, Mihindukulasuriya, Kathie A, Wang, Leran, Paredes, Anne, Cárdenas, Luis Alberto Chica, Henry-Cocks, Kara, Lima, Lais Farias Oliveira, Dinsdale, Elizabeth A, Edwards, Robert A, Handley, Scott A
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 02-01-2024
• Subjects: Animals; Annotations; Computational Biology - methods; Coral reefs; Data analysis; Genome, Viral; Integrated software; Metagenome; Metagenomics; Metagenomics - methods; Quality control; Sequences; Software; Statistical analysis; Task complexity; Technical Note; Virome - genetics; Viruses - classification; Viruses - genetics; Workflow; virome; virus discovery; viral metagenomics; bioinformatic workflow
• ISSN: 2047-217X; 2047-217X
• DOI: 10.1093/gigascience/giae020

Abstract
Background
Modern sequencing technologies offer extraordinary opportunities for virus discovery and virome analysis. Annotation of viral sequences from metagenomic data requires a complex series of steps to ensure accurate annotation of individual reads and assembled contigs. In addition, varying study designs will require project-specific statistical analyses.
Findings
Here we introduce Hecatomb, a bioinformatic platform coordinating commonly used tasks required for virome analysis. Hecatomb means “a great sacrifice.” In this setting, Hecatomb is “sacrificing” false-positive viral annotations using extensive quality control and tiered-database searches. Hecatomb processes metagenomic data obtained from both short- and long-read sequencing technologies, providing annotations to individual sequences and assembled contigs. Results are provided in commonly used data formats useful for downstream analysis. Here we demonstrate the functionality of Hecatomb through the reanalysis of a primate enteric and a novel coral reef virome.
Conclusion
Hecatomb provides an integrated platform to manage many commonly used steps for virome characterization, including rigorous quality control, host removal, and both read- and contig-based analysis. Each step is managed using the Snakemake workflow manager with dependency management using Conda. Hecatomb outputs several tables properly formatted for immediate use within popular data analysis and visualization tools, enabling effective data interpretation for a variety of study designs. Hecatomb is hosted on GitHub (github.com/shandley/hecatomb) and is available for installation from Bioconda and PyPI.