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Abstract Single-cell genomics enables cell-resolved insights into in-situ microbial communities, yet single amplified genomes (SAGs) are often fragmented, taxonomically ambiguous, and prone to contamination, limiting their biological interpretation. Here, we present Scellmate, a scalable, semi-supervised framework that integrates whole-SAG curation, species-level taxonomic anchoring and SAG–mobilome linkage analysis for large-scale SAG datasets.
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