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

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

Abstract 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 clu...

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Main Authors: Xiaowei Zhuang, Van Vo, Michael A. Moshi, Ketan Dhede, Nabih Ghani, Shahraiz Akbar, Ching-Lan Chang, Angelia K. Young, Erin Buttery, William Bendik, Hong Zhang, Salman Afzal, Duane Moser, Dietmar Cordes, Cassius Lockett, Daniel Gerrity, Horng-Yuan Kan, Edwin C. Oh
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-61280-5
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https://doi.org/10.1038/s41467-025-61280-5

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