Coordinate and integrate multiple omics datasets for comprehensive systems biology analysis. This skill orchestrates specialized ToolUniverse skills to perform cross-omics correlation, multi-omics clustering, pathway-level integration, and unified interpretation across molecular layers.
| 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 |
Integrate and analyze multiple omics datasets (transcriptomics, proteomics, epigenomics, genomics, metabolomics) for systems biology and precision medicine. Performs cross-omics correlation, multi-omics clustering (MOFA+, NMF), pathway-level integration, and sample matching. Coordinates ToolUniverse skills for expression data (RNA-seq), epigenomics (methylation, ChIP-seq), variants (SNVs, CNVs), protein interactions, and pathway enrichment. Use when analyzing multi-omics datasets, performing integrative analysis, discovering multi-omics biomarkers, studying disease mechanisms across molecular layers, or conducting systems biology research that requires coordinated analysis of transcriptome, genome, epigenome, proteome, and metabolome data. Source: mims-harvard/tooluniverse.