Tooluniverse Multiomic Disease Characterization

This is a structured pipeline for pulling together genomics, transcriptomics, proteomics, and pathway data on a disease to build a systems-level picture. It runs nine phases: disease disambiguation first, then layer-by-layer analysis (GWAS hits, gene expression, PPI networks, pathway enrichment, GO terms), followed by cross-layer integration to spot genes that show up across multiple omics types. The skill calculates a multi-omics confidence score and flags druggable targets and biomarker candidates. You'd use this when you need a full molecular workup of a disease rather than chasing a single gene or drug. It's designed to catch concordance across layers, which strengthens findings, and discordance, which reveals regulatory complexity.