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BGC-QUAST: a quality assessment tool for genome mining software

Kushnareva, A.; Tupikina, D.; Almessady, H.; McHardy, A.; Gurevich, A.

2026-05-07 bioinformatics
10.64898/2026.05.04.722653 bioRxiv
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SummaryBiosynthetic gene clusters (BGCs) encode microbial natural products, many of which have important ecological and biomedical roles. Genome mining tools enable large-scale BGC prediction, but their outputs differ substantially, complicating comparison and interpretation. We present BGC-QUAST, a framework for evaluating and comparing BGC predictions across three analysis modes: comparison across samples, assessment of BGC recovery in draft assemblies relative to reference genomes, and comparison of predictions from different tools using overlap analysis. BGC-QUAST provides standardized metrics, interactive visualizations, and integrated outputs for joint inspection of predictions, enabling the comprehensive comparison of genome mining results and facilitating sample prioritisation based on biosynthetic potential. Availability and implementationBGC-QUAST is publicly available at https://github.com/gurevichlab/bgc-quast

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