Medical-research-skills reactome-skill

Query the Reactome REST API for pathway content and enrichment analyses; use when you need curated pathway data, reaction details, or overrepresentation results for a gene list.

install

source · Clone the upstream repo

git clone https://github.com/aipoch/medical-research-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/aipoch/medical-research-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/scientific-skills/Evidence Insight/reactome-skill" ~/.claude/skills/aipoch-medical-research-skills-reactome-skill && rm -rf "$T"

manifest: scientific-skills/Evidence Insight/reactome-skill/SKILL.md

source content

Source: https://github.com/aipoch/medical-research-skills

When to Use

You have a list of genes/proteins and want to run pathway overrepresentation (enrichment) analysis against Reactome.
You need to retrieve curated pathway content (hierarchy, reactions, participants) by Reactome stable IDs (e.g.,
```
R-HSA-69278
```
).
You want to map expression values onto pathways to support pathway-level interpretation.
You need to project pathways across species/organisms using Reactome’s species projection capabilities.
You are building a systems biology workflow that requires programmatic access to Reactome via its REST API.

Key Features

Pathway enrichment (overrepresentation) for identifier lists.
Expression analysis by mapping expression data to Reactome pathways.
Content retrieval for pathways, reactions, and participating molecules.
Pathway hierarchy access to navigate curated pathway structures.
Species projection to map pathways across organisms.
API documentation reference: see
```
references/api_reference.md
```
.

Dependencies

```
python
```
(3.x)
```
requests
```
(latest compatible)
```
reactome2py
```
(latest compatible)

Install:

uv pip install reactome2py requests

Example Usage

The following commands are runnable examples using the provided CLI script.

1) Query pathway content by Reactome ID

python scripts/reactome_tool.py query_content --id "R-HSA-69278"

2) Run overrepresentation analysis for a gene list

python scripts/reactome_tool.py analyze_identifiers --identifiers "TP53,BRCA1"

Implementation Details

API access pattern: The skill uses the Reactome REST API (via
```
reactome2py
```
and/or direct HTTP calls with
```
requests
```
) to fetch pathway content and submit analyses.
Identifier input: Gene/protein identifiers are provided as a comma-separated string (e.g.,
```
TP53,BRCA1
```
) and are submitted for overrepresentation analysis.
Stable IDs: Content retrieval expects Reactome stable identifiers (commonly formatted like
```
R-HSA-xxxxx
```
for human pathways).
Outputs: Results typically include pathway/reaction metadata and analysis outputs (e.g., enriched pathways with associated statistics), depending on the invoked action.
Reference: Reactome developer documentation is available at https://reactome.org/dev and the local API notes at
```
references/api_reference.md
```
.