HI-FEVER: a Nextflow pipeline for the high-throughput discovery and annotation of endogenous viral elements

Journal article

Summary: Endogenous viral elements (EVEs) offer valuable insights into virus and host evolution, but their detection remains computationally and biologically challenging. We present HI-FEVER, a user-friendly Nextflow pipeline for the discovery of EVEs in eukaryotic host genomes. HI-FEVER is highly parallelizable and customizable, ensuring computational efficiency while allowing researchers to fine-tune parameters to their specific needs. Its output provides a comprehensive analysis of discovered EVEs, including detailed annotations which can provide evolutionary insights. HI-FEVER scales seamlessly to handle millions of viral protein queries across multiple host genomes on both laptops and high-performance computing nodes. Availability and implementation: The HI-FEVER source code is available on GitHub at https://github.com/PaleovirologyLab/hi-fever. Minimal reference databases, test datasets and benchmarking results are hosted on the Open Science Framework at https://osf.io/y357r. A detailed wiki is available at https://github.com/PaleovirologyLab/hi-fever/wiki, including usage instructions, parameter descriptions, and guidance on interpreting outputs. The pipeline includes a Pixi environment compatible with Conda and Apptainer containerization, and Docker images. HI-FEVER has been tested on Linux, Windows (via WSL2), and macOS (Intel and ARM64).

Authors: Muñoz-Baena, L; Harding, EF; Nino Barreat, JG; Kinsella, CM; Katzourakis, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: Bioinformatics
• Volume: 41
• Issue: 12
• Pages: btaf610
• Article number: btaf610
• Publication date: 2025-11-08
• Acceptance date: 2025-10-08
• DOI: 10.1093/bioinformatics/btaf610
• EISSN: 1367-4811
• ISSN: 1367-4803
• Language: English