CAGEcleaner: reducing genomic redundancy in gene cluster mining.

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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.\nAVAILABILITY AND IMPLEMENTATION: 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).", "claims": [{"id": "claim-method", "statement": "The second strategy assesses the cblaster homology scores of each gene cluster hit. Within each subgroup, hits with outlier scores as identified using z-scoring, are retained, ensuring that functionally distinct gene clusters are not removed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40566668", "locator": "sections[2] \"2 Implementation\" paragraph 6", "quote": "The second strategy assesses the cblaster homology scores of each gene cluster hit. 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