MetaScope: A High-Resolution Framework for Species-Level 16S Metataxonomic Classification

Abstract

Accurate species-level classification of microbial communities remains a major challenge in microbiome analysis, particularly when using traditional 16S rRNA amplicon sequencing pipelines such as QIIME2 and DADA2. These methods often fail to resolve taxonomy beyond the genus level due to limitations in clustering algorithms and ambiguous marker genes. To address this, we present MetaScope, a modular, R-based software package that reimplements and extends the PathoScope 2.0 framework for high-resolution microbial classification. MetaScope introduces two key innovations: (1) the integration of user-defined or empirical prior weights into the Bayesian read reassignment algorithm to improve abundance estimation, and (2) MetaBlast, a secondary BLAST-based validation module for refining species-level assignments. Benchmarking against mock and clinical datasets demonstrates that MetaScope significantly outperforms QIIME2 and DADA2, achieving up to 93.6% species-level classification accuracy. This translates to offering enhanced resolution for downstream analyses such as ecological diversity metrics. These results highlight MetaScope as a powerful tool for advancing microbial community profiling in both research and clinical settings.