gget

Name: gget
Availability: InStock
Author: Engstrom

Query genomic databases via CLI and Python interfaces for gene discovery and enrichment.

18|1|Updated Dec 27, 2025

Search Tags:#python #cli #bioinformatics #genomics #data-analysis #databases #enrichment

Ready to run

npx skills add https://github.com/LogauaEngstrom/claude-scientific-skills --skill gget-logauaengstrom

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gget
Source: https://github.com/LogauaEngstrom/claude-scientific-skills/tree/main/scientific-skills/gget
Command: npx skills add https://github.com/LogauaEngstrom/claude-scientific-skills --skill gget-logauaengstrom

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, and includes scripts (resource) and references (resource) components.

What problem does it solve?

The tool unifies access to numerous genomic data resources, enabling researchers to perform discovery, retrieval, and data integration from a single interface.

Core Features & Use Cases

CLI & Python interfaces for 20+ databases (Ensembl, UniProt, ARCHS4, OpenTargets, PDB, etc.) and analysis methods.
Unified workflows for gene discovery, sequence retrieval, enrichment, and disease/drug associations across species.
Use Case: A researcher quickly finds gene descriptions, fetches sequences, and performs enrichment on a list of candidate genes in one session.

Quick Start

Run a quick gene search using gget to explore BRCA1 in Homo sapiens.

Frequently Asked Questions about gget

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

FAQPage Schema

How do I query multiple genomic databases like Ensembl and UniProt from a single Python script?▼

You can query genomic databases from a single interface using Python and CLI APIs to retrieve gene info, sequences, and expression data across Ensembl, UniProt, and others. This unifies access to simplify data integration workflows.

Can I perform gene enrichment analysis on a list of candidate genes using the command line?▼

Yes, gene enrichment analysis can be performed directly via the command line. The CLI interface supports enrichment workflows alongside gene discovery, allowing you to process candidate gene lists rapidly in one session.

Does this genomic data query tool require pandas to fetch sequences and expression data?▼

Pandas is required as a dependency to operate the genomic data query tool. It facilitates the data analysis and integration of sequences, expression data, and disease associations retrieved from the supported databases.

What is the best way to fetch gene sequences and disease associations across different species?▼

The best way to fetch gene sequences and disease associations across species is using a unified query interface. It provides modular, scriptable access to databases like OpenTargets and PDB for rapid discovery and retrieval.

How do I retrieve OpenTargets and ARCHS4 gene expression data for bioinformatics research?▼

To retrieve ARCHS4 and OpenTargets gene expression data for bioinformatics research, use the modular Python or CLI interfaces. These provide robust error handling and reproducible workflows for querying expression data directly.

Are there limitations when integrating COSMIC and OpenTargets data for genomics data-analysis?▼

The tool integrates COSMIC and OpenTargets data for genomics data-analysis without specified limitations, offering robust error handling and documentation. It targets researchers needing reproducible workflows across supported databases.