Which identifier types does this Reactome skill support?

The skill supports a wide range of biological identifiers including UniProt accessions, Gene symbols, Ensembl IDs, EntrezGene IDs, and ChEBI IDs for small molecules.

Does this skill allow for visual data exploration?

Yes, it can generate specific URLs that load your analysis results directly into the Reactome Pathway Browser for interactive visualization.

Can I perform quantitative expression analysis with this skill?

Yes, you can submit TSV-formatted expression data with a header row to identify relevant pathways based on numeric expression values across multiple samples.

Is a local database installation required?

No, this skill communicates directly with Reactome's live REST API endpoints, ensuring you always access the most up-to-date pathway data.

How long do the pathway analysis results remain available?

Analysis tokens generated through the Reactome Analysis Service are valid for 7 days, allowing you to retrieve results without re-submitting data.

Reactome Pathway Analysis

Name: Reactome Pathway Analysis
Author: sanand0

bysanand0

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Data Science & ML

Performs comprehensive biological pathway analysis and gene-to-pathway mapping using the Reactome open-source database.

About

This skill integrates Claude with the Reactome REST API and reactome2py Python library to facilitate advanced systems biology research. It enables researchers to perform overrepresentation and expression analysis on gene or protein lists, query specific molecular interactions, and explore curated human pathways. By automating the retrieval of pathway hierarchies and mapping entities across various identifier types, this skill transforms raw genomic data into actionable biological insights and provides direct links to the Reactome Pathway Browser for visual exploration.

Key Features

Mapping of multiple identifier types including UniProt, Ensembl, EntrezGene, and ChEBI
4 GitHub stars
Quantitative expression data analysis with statistical metrics including FDR and p-values
Seamless integration with the Reactome Analysis and Content REST API services
Automated overrepresentation analysis to identify enriched biological pathways
Detailed retrieval of molecular interactions, reactions, and pathway hierarchies

Use Cases

Identifying statistically significant pathways from differential gene expression results
Conducting comparative pathway analysis and species projection across organisms
Mapping custom gene sets to specific disease mechanisms and metabolic processes

About

Key Features

Mapping of multiple identifier types including UniProt, Ensembl, EntrezGene, and ChEBI
4 GitHub stars
Quantitative expression data analysis with statistical metrics including FDR and p-values
Seamless integration with the Reactome Analysis and Content REST API services
Automated overrepresentation analysis to identify enriched biological pathways
Detailed retrieval of molecular interactions, reactions, and pathway hierarchies

Use Cases

Identifying statistically significant pathways from differential gene expression results
Conducting comparative pathway analysis and species projection across organisms
Mapping custom gene sets to specific disease mechanisms and metabolic processes