What format should expression data be in?

Expression data should be in TSV format with a header row starting with a '#' character, followed by columns for identifiers and numeric expression values.

Can I perform pathway analysis for species other than humans?

Yes, while Reactome is human-centric, the skill supports species projection which maps identifiers from other organisms to human pathways for comparative analysis.

What types of identifiers does this skill support?

The skill supports multiple identifier types including UniProt accessions, Gene symbols, Ensembl IDs, EntrezGene IDs, and ChEBI IDs for small molecules.

Is the reactome2py Python package mandatory for this skill?

No, the skill can perform all operations using direct REST API calls to the Reactome Content and Analysis services if the Python package is not installed.

How long are analysis results valid?

Analysis tokens generated by the Reactome Analysis Service are valid for 7 days, allowing you to retrieve results across sessions without re-submission.

Reactome Database Integration

Name: Reactome Database Integration
Author: lingxling

bylingxling

•

Ciencia de Datos y ML

Integrates biological pathway analysis and molecular interaction data from the open-source Reactome database into systems biology workflows.

The Reactome Database skill empowers Claude to perform advanced systems biology research by providing direct access to over 2,800 human biological pathways. It enables users to map gene or protein lists to specific pathways, perform statistical overrepresentation analysis, and analyze quantitative expression data via the Reactome REST API and Python client. This skill is ideal for researchers and bioinformaticians who need to visualize molecular interactions, explore disease mechanisms, or conduct comparative pathway analysis across species directly within their development environment.

Características Principales

01Direct integration with the Reactome Pathway Browser via generated analysis tokens

02Deep querying of molecular interactions, reactions, and pathway hierarchies

03Automated pathway overrepresentation analysis for gene and protein lists

04Cross-species comparative pathway projection and orthology mapping

0539 GitHub stars

06Statistical analysis of gene expression data to identify relevant biological processes

Casos de Uso

01Mapping protein-protein interactions to understand specific human disease mechanisms

02Identifying enriched biological pathways in a set of differentially expressed genes

03Generating visualization URLs for complex biological data analysis results

Características Principales

01Direct integration with the Reactome Pathway Browser via generated analysis tokens

02Deep querying of molecular interactions, reactions, and pathway hierarchies

03Automated pathway overrepresentation analysis for gene and protein lists

04Cross-species comparative pathway projection and orthology mapping

0539 GitHub stars

06Statistical analysis of gene expression data to identify relevant biological processes

Casos de Uso

01Mapping protein-protein interactions to understand specific human disease mechanisms

02Identifying enriched biological pathways in a set of differentially expressed genes

03Generating visualization URLs for complex biological data analysis results