Workflow from Scientific Research

Schematic overview of the use of NPClassScore in integrative omics mining where functionality that previously existed in the NPLinker workflow is shaded in grey. First, BGCs and MS/MS spectra are clustered and dereplicated by BiG-SCAPE and GNPS molecular networking, respectively. Co-occurrence scoring (standardised Metcalf) is used to generate ranked candidate links of BGC-MS/MS spectra by correlating the presence/absence patterns of strains that contain a BGC and/or MS/MS spectrum. Depicted in the non-shaded area is the NPClassScore workflow which we integrated in the NPLinker platform. We incorporated structure-based classification predictions into the integrative omics mining workflow using CANOPUS from the SIRIUS platform and MolNetEnhancer, which predict ClassyFire and NPClassifier ontologies, while using antiSMASH and BiG-SCAPE for genome-based chemical compound classification ontologies. Based on the predicted classes of a BGC and MS/MS spectrum, NPClassScore outputs a score based on the matched genome- and structure-based ontologies in MIBiG. The best use of the scores from NPClassScore is to filter candidate BGC-MS/MS spectrum links based on a NPClassScore cut-off and then rerank the previously ranked candidate lists resulting from co-occurrence scoring

DOI