CAGEcleaner: reducing genomic redundancy in gene cluster mining.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 40566668.
- Also identified by DOI 10.1093/bioinformatics/btaf373 and PMC identifier 12263103.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Mining homologous biosynthetic gene clusters (BGCs) typically involves searching colocalised genes against large genomic databases. However, the high degree of genomic redundancy in these databases often propagates into the resulting hit sets, complicating downstream analyses and visualization. To address this challenge, we present CAGEcleaner, a Python-based pipeline with auxiliary bash scripts designed to reduce redundancy in gene cluster hit sets by dereplicating the genomes that host these hits. CAGEcleaner integrates seamlessly with widely used gene cluster mining tools, such as cblaster and CAGECAT, enabling efficient filtering and streamlining BGC discovery workflows. Source code and documentation is hosted at GitHub (https://github.com/LucoDevro/CAGEcleaner) and Zenodo (https://doi.org/10.5281/zenodo.14726119) under an MIT license. For accessibility, CAGEcleaner is installable from Bioconda (https://anaconda.org/bioconda/cagecleaner) and PyPi (https://pypi.org/project/cagecleaner/), and is also available as a Docker image from DockerHub (https://hub.docker.com/r/lucodevro/cagecleaner).
Medical subject headings
- Software
- Multigene Family
- Data Mining
- Genomics