PREMISE: A Quality-Aware Probabilistic Framework for Pathogen Resolution and Source Assignment in Viral mNGS
The paper introduces PREMISE, a high-performance, quality-aware probabilistic framework that utilizes alignment-based Expectation-Maximization to overcome the limitations of k-mer methods, enabling accurate identification of viral subtypes, estimation of relative abundances, and detection of complex events like reassortment and recombination in Influenza A viruses from metagenomic sequencing data.