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

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Input

Required Files

File	Format	Description
INLINECODE0	CSV	Transcriptomics data: Gene ID, expression value, differential analysis results
INLINECODE1

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)

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Protein Data (pro_data.csv)

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Metabolite Data (met_data.csv)

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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

Supported databases:

• - KEGG (Kyoto Encyclopedia of Genes and Genomes)
• Reactome
• WikiPathways
• GO (Gene Ontology) - Biological Process

3. Cross-Validation Methods

3.1 Directional Consistency Validation

• - Whether the change direction of genes/proteins/metabolites in the same pathway is consistent
• Score: +1 (consistent), -1 (opposite), 0 (no data)

3.2 Correlation Validation

• - Pearson/Spearman correlation analysis
• Cross-omics expression profile clustering

3.3 Pathway Enrichment Concordance

• - Independent enrichment analysis for each omics
• Common enriched pathway identification

3.4 Network Topology Validation

• - Construct cross-omics regulatory network
• Identify key nodes (Hub genes/proteins/metabolites)

Output

1. Integration Report (integration_report.md)

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2. External Visualization Tools (Not Included)

This tool generates analysis results that can be visualized using external tools. Users may export results to:

Chart Type	Purpose	External Tool Required
Circos Plot	Cross-omics relationship panorama	matplotlib/circlize (user-installed)
Pathway Heatmap

Pathway-level changes | seaborn/complexheatmap (user-installed) |
| Sankey Diagram | Data flow mapping | plotly (user-installed) |
| Network Graph | Molecular interaction network | networkx/cytoscape (networkx is included) |
| Correlation Matrix | Cross-omics correlation | seaborn (user-installed) |
| Bubble Plot | Integrated enrichment analysis | ggplot2/plotly (user-installed) |

Note: This skill focuses on data integration and analysis. Visualization requires separate installation of plotting libraries by the user.

3. Output Files

File	Description
INLINECODE4	ID mapping results
INLINECODE5

Pathway cross-validation scores | | consistency_matrix.csv | Cross-omics consistency matrix | | network_edges.csv | Network edge list | | report.html | Interactive HTML report |

Usage

Basic Usage

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Advanced Options

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Configuration

config/pathways.json

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Dependencies

• - Python >= 3.8
• pandas >= 1.3.0
• numpy >= 1.21.0
• scipy >= 1.7.0
• scikit-learn >= 1.0.0
• networkx >= 2.6.0
• matplotlib >= 3.4.0
• seaborn >= 0.11.0
• gseapy >= 1.0.0 (Pathway enrichment analysis)

References

1. 1. Subramanian et al. (2005) PNAS - GSEA method
2. Kamburov et al. (2011) NAR - ConsensusPathDB
3. Chin et al. (2018) Nature Communications - Multi-omics integration methods review

Version

• - Version: 1.0.0
• Last Updated: 2026-02-06
• Author: OpenClaw Bioinformatics Team

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access

No external API calls | Low | | File System Access | Read input files, write output files | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output files saved to workspace | Low |

Security Checklist

• - [ ] No hardcoded credentials or API keys
• [ ] No unauthorized file system access (../)
• [ ] Output does not expose sensitive information
• [ ] Prompt injection protections in place
• [ ] Input file paths validated (no ../ traversal)
• [ ] Output directory restricted to workspace
• [ ] Script execution in sandboxed environment
• [ ] Error messages sanitized (no stack traces exposed)
• [ ] Dependencies audited

Prerequisites

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Evaluation Criteria

Success Metrics

• - [ ] Successfully executes main functionality
• [ ] Output meets quality standards
• [ ] Handles edge cases gracefully
• [ ] Performance is acceptable

Test Cases

1. 1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• - Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:

- Performance optimization - Additional feature support

Parameters

Parameter	Type	Default	Description
INLINECODE9	str	Required
INLINECODE10

str | Required | | | --met | str | Required | | | --output | str | './results' | | | --databases | str | 'KEGG' | | | --create-sample | str | Required | Create sample data for testing | | --format | str | 'md | |