Ultrafast alignment-free detection of viral genome variation with bronko.

bronko detects viral genome variation from sequencing data with near-linear scaling, running up to one to three orders of magnitude faster while recovering variants with higher precision on simulated amplicon sequencing.

• Why it matters: Alignment-based variant calling is becoming computationally prohibitive as viral sequencing datasets grow, limiting scalable detection of minor variants and mutation-dense regions.
• What they did: bronko combines locality-sensitive bucketing for SNPs, k-mer pseudo-mapping without alignment, greedy de novo assembly for indels, and a streaming sliding-window outlier test to separate real minor variants from baseline noise.
• The result: In simulated amplicon data, it achieves higher precision with comparable recall; in chronically infected SARS-CoV-2 patients, it reveals consistent intrahost diversification and adaptive mutations over time.

AI summary of the abstract · may contain errors · not medical advice · read the paper.