AI-Powered Novel Virus Detection from Wastewater

Greenseq Oy Ltd developed WastHAI an AI-based solution for identifying novel viruses in wastewater using unsupervised machine learning. Recognizing that viral sequencing data is typically noisy and diverse the team designed a robust pipeline leveraging public sequencing data from NCBI’s PRJNA966185 project and the Twist Biosciences Comprehensive Viral Panel. Instead of using nucleotide sequences as input—unreliable due to random alignment points—they derived virus-specific features such as alignment score distributions and sequence replication counts. Using dimensionality reduction (t-SNE) and clustering (DBSCAN)

Detection of novel or re-emerging viral pathogens by applying unsupervised learning and outlier detection on virus-enriched sequencing datasets derived from wastewater enabling early health surveillance