| name | multi-omics-integration-strategist |
| description | Design multi-omics integration strategies for transcriptomics, proteomics, and metabolomics data analysis |
| version | 1.0.0 |
| category | Bioinfo |
| tags | [] |
| author | AIPOCH |
| license | MIT |
| status | Draft |
| risk_level | Medium |
| skill_type | Tool/Script |
| owner | AIPOCH |
| reviewer | |
| last_updated | 2026-02-06 |
Skill: Multi-Omics Integration Strategist (ID: 204)
Overview
Designs multi-omics (transcriptomics RNA, proteomics Pro, metabolomics Met) joint analysis schemes, performs cross-validation at the pathway level, and provides systems biology-level integrated analysis strategies.
Use Cases
- Systems biology mechanism research for complex diseases
- Biomarker discovery and validation
- Drug target identification and pathway validation
- Multi-omics data quality assessment and consistency analysis
Directory Structure
.
├── SKILL.md # This file - Skill documentation
├── config/
│ └── pathways.json # Pathway database configuration
├── scripts/
│ └── main.py # Main analysis script
├── templates/
│ └── report_template.md # Analysis report template
└── examples/
└── sample_data/ # Sample datasets
Input
Required Files
| File | Format | Description |
|---|
rna_data.csv | CSV | Transcriptomics data: Gene ID, expression value, differential analysis results |
pro_data.csv | CSV | Proteomics data: Protein ID, abundance value, differential analysis results |
met_data.csv | CSV | Metabolomics data: Metabolite ID, concentration value, differential analysis results |
Input Format Specifications
RNA Data (rna_data.csv)
gene_id,gene_name,log2fc,pvalue,padj,sample_A,sample_B,...
ENSG00000139618,BRCA1,1.23,0.001,0.005,12.5,13.2,...
Protein Data (pro_data.csv)
protein_id,gene_name,log2fc,pvalue,padj,sample_A,sample_B,...
P38398,BRCA1,0.85,0.002,0.008,2450,2890,...
Metabolite Data (met_data.csv)
metabolite_id,metabolite_name,kegg_id,log2fc,pvalue,padj,...
C00187,Cholesterol,C00187,-1.45,0.003,0.012,...
Integration Strategy
1. ID Mapping Layer
- RNA → Protein: Mapping through Gene Symbol / UniProt ID
- Protein → Metabolite: Association through KEGG/Reactome enzyme-reaction-metabolite
- RNA → Metabolite: Indirect association through KEGG pathway
2. Pathway Mapping
