scientific-ontology-enrichment

Integrate EFO, OLS, Enrichr, and UMLS to map experimental factors and enrich gene lists.

3|1|Updated Feb 11, 2026

Search Tags:#ontology #bioinformatics #enrichment #ols #enrichr #efo #umls

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-ontology-enrichment

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-ontology-enrichment
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-ontology-enrichment
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-ontology-enrichment

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This pipeline enables mapping biomedical experiment factors to standardized ontology terms and performing cross-ontology enrichment analyses by integrating EFO, OLS, Enrichr, and UMLS.

Core Features & Use Cases

Ontology mapping: map experimental factors to EFO terms and retrieve cross-ontology mappings via OLS and UMLS.
Gene-set enrichment: run enrichment analyses on gene lists with Enrichr across multiple libraries.
Cross-ontology search: perform cross-ontology queries across HP, MONDO, DOID, GO, CHEBI, and related resources.

Quick Start

Provide a gene list and run the integrated ontology enrichment pipeline to obtain ontology mappings and enrichment results.

Frequently Asked Questions about scientific-ontology-enrichment

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform cross-ontology enrichment analysis for gene lists?▼

Cross-ontology enrichment analysis integrates EFO, OLS, Enrichr, and UMLS to map biomedical experimental factors to standardized ontology terms and run enrichment queries across multiple libraries. You provide a gene list to obtain ontology mappings and enrichment results for downstream bioinformatics analyses.

What is cross-ontology mapping and when do I need it for bioinformatics workflows?▼

Cross-ontology mapping links experimental factors to standardized terms across HP, MONDO, DOID, GO, and CHEBI using OLS and UMLS. You need it when your bioinformatics workflow requires consistent annotation and cross-ontology queries across disparate biomedical resources.

Can I use Enrichr and EFO mappings together in a single ontology enrichment pipeline?▼

Yes, you can use Enrichr and EFO mappings together within a single pipeline. The skill integrates EFO for experimental factor annotation and Enrichr for gene-set enrichment, outputting combined ontology mappings and enrichment results for your downstream analyses.

Do I need API access to run cross-ontology queries across UMLS and OLS?▼

Yes, you need API access to EFO, OLS, UMLS, and Enrichr to run cross-ontology queries. The pipeline requires these external ontology services to retrieve standardized mappings and perform enrichment analyses across biomedical resources.

What is the best way to map experimental factors to standardized ontology terms?▼

The best way to map experimental factors to standardized ontology terms is using an integrated pipeline that applies EFO, OLS, and UMLS. This approach retrieves cross-ontology mappings across resources like MONDO and GO, ensuring consistent annotation for enrichment analyses.

Are there limitations when performing cross-ontology enrichment with EFO and UMLS?▼

Limitations of cross-ontology enrichment include dependency on external API availability for EFO, OLS, UMLS, and Enrichr. If an API is unavailable, the pipeline cannot retrieve the ontology mappings or enrichment results needed for your downstream bioinformatics analyses.