MagmaFlow: A desktop platform for artificial intelligence-driven expression analysis

While simplistic volcano plot visualizations of multi-omics changes can highlight the most critical genomic, transcriptomic, or proteomic features, integrative frameworks combining literature evidence, pathway associations, and functional annotation remain limited. We present MagmaFlow, a cross-platform application offering three key capabilities: literature-based gene scoring, interactive pathway-to-volcano mapping, and synchronized cross-view updates. The literature module retrieves gene associations from PubMed via PubTator3, provides direct PubMed identifier (PMID) links, and ranks genes by context-specific relevance. The pathway module visualizes enrichment as multi-layer circle plots displaying cross-pathway membership, automatically synchronized with volcano selections. Interactive features include smart label positioning, drag-and-drop annotation, double-click gene targeting, and customizable styles for publication-quality figures. Thus, MagmaFlow transforms volcano plot analysis from static display into dynamic biological interpretation. To our knowledge, this is the first tool integrating artificial intelligence-powered literature contextualization and enrichment analysis to convert differential expression data into actionable insights.