tooluniverse-multi-omics-integration

When to Use This Skill

Triggers:

• User has multiple omics datasets (RNA-seq + proteomics, methylation + expression, etc.)
• Requests for integrative multi-omics analysis
• Cross-omics correlation queries (e.g., "How does methylation affect expression?")
• Multi-omics biomarker discovery
• Systems biology questions requiring multiple molecular layers
• Precision medicine applications with multi-omics patient data
• Questions about molecular mechanisms across omics types

Example Questions This Skill Solves:

1. "Integrate RNA-seq and proteomics data to find genes with concordant changes"
2. "How does promoter methylation correlate with gene expression?"
3. "Perform multi-omics clustering to identify patient subtypes"
4. "Which pathways are dysregulated across transcriptome, proteome, and metabolome?"
5. "Find multi-omics biomarkers for disease classification"
6. "Correlate CNV with gene expression to identify dosage effects"
7. "Integrate GWAS variants, eQTLs, and expression data"
8. "Perform MOFA+ analysis on multi-omics cancer data"

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Core Capabilities

Capability	Description
Data Integration	Match samples across omics, handle missing data, normalize scales
Cross-Omics Correlation	Correlate features across molecular layers (gene expression vs protein, methylation vs expression)
Multi-Omics Clustering	MOFA+, NMF, joint clustering to identify omics-driven subtypes
Pathway Integration	Combine omics evidence at pathway level for unified biological interpretation
Biomarker Discovery	Identify multi-omics signatures with improved predictive power
Skill Coordination	Orchestrate RNA-seq, epigenomics, variant-analysis, protein-interactions, gene-enrichment skills
Visualization	Circos plots, integrated heatmaps, network visualizations
Reporting	Unified multi-omics reports with cross-layer insights

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