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Article

Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning.

Nature communications - 8 Jul 2025

Zhuang Xiaowei, Vo Van, Moshi Michael A, Dhede Ketan, Ghani Nabih, Akbar Shahraiz, Chang Ching-Lan, Young Angelia K, Buttery Erin, Bendik William, Zhang Hong, Afzal Salman, Moser Duane, Cordes Dietmar, Lockett Cassius, Gerrity Daniel, Kan Horng-Yuan, Oh Edwin C

Abstract excerpt

Genome sequencing from wastewater enables accurate and cost-effective identification of SARS-CoV-2 variants. However, existing computational pipelines have limitations in detecting emerging variants not yet characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns to identify SARS-CoV-2 variants. To build our model, we sequence 3659...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 40623990
DOI: 10.1038/s41467-025-61280-5
PMCID: PMC12234891

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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