beams-BGC

BGCFlow is the standard pipeline for mining biosynthetic gene clusters (BGCs) across bacterial pangenomes, but its output is hard to interpret without expert time, and every novelty-relevant stage (antiSMASH, MIBiG, Pfam, GTDB) can only recognize what already resembles something known — homology-matching is the ceiling. We built two additive tools to break past it. BGCLens is a read-only layer that ingests a finished BGCFlow project, recommends and runs the right statistics (PCoA, PERMANOVA, enrichment, diversity), renders figures, and writes plain-English interpretations via a guarded LLM pass that strips any invented numbers or accessions. BGCFlow-PLM adds an ESM2 protein-language-model side-channel that flags biosynthetic-core proteins with no close MIBiG neighbor — a remote-homology novelty axis the databases miss — without ever touching an antiSMASH call. Together they lower the expertise barrier to acting on genome-mining results and help researchers surface genuinely novel candidates instead of only re-finding the already-catalogued.