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.

skills.sh installs: 360
GitHub stars: 1.8K
last updated: Aug 21, 2026

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Install

$ npx -y skills add mims-harvard/tooluniverse --skill tooluniverse-multiomic-disease-characterization --agent claude-code

Installs into .claude/skills of the current project.

Files

Multi-Omics Disease Characterization Pipeline

Characterize diseases across multiple molecular layers (genomics, transcriptomics, proteomics, pathways) to provide systems-level understanding of disease mechanisms, identify therapeutic opportunities, and discover biomarker candidates.

SKILL.md on GitHub

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