| Title: |
HI-FEVER: a Nextflow pipeline for the high-throughput discovery and annotation of endogenous viral elements |
| Authors: |
Muñoz-Baena, Laura; Harding, Emma F; Nino Barreat, Jose Gabriel; Kinsella, Cormac M; Katzourakis, Aris |
| Contributors: |
Nikolski, Macha; European Research Council |
| Source: |
Bioinformatics ; volume 41, issue 12 ; ISSN 1367-4811 |
| Publisher Information: |
Oxford University Press (OUP) |
| Publication Year: |
2025 |
| Description: |
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). |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1093/bioinformatics/btaf610 |
| DOI: |
10.1093/bioinformatics/btaf610/65246986/btaf610.pdf |
| Availability: |
https://doi.org/10.1093/bioinformatics/btaf610; https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaf610/65246986/btaf610.pdf; https://academic.oup.com/bioinformatics/article-pdf/41/12/btaf610/65246986/btaf610.pdf |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.9BDD388A |
| Database: |
BASE |