Is gget suitable for large-scale batch processing?

While gget is optimized for speed and ease of use, for very large batch processing or advanced BLAST parameters, it is often used alongside specialized libraries like Biopython.

Does this skill require additional setup?

Basic modules work immediately, but advanced features like AlphaFold, ELM, and cellxgene require a simple one-time setup command to install specific dependencies.

What databases does the gget skill support?

gget provides access to over 20 databases including Ensembl, UniProt, NCBI, RCSB PDB, ARCHS4, and CZ CELLxGENE for comprehensive biological research.

Can I use gget for protein structure prediction?

Yes, the skill includes a module for AlphaFold2 which allows for 3D protein structure prediction directly from amino acid sequences within your workflow.

Bioinformatics & Genomic Data (gget)

Name: Bioinformatics & Genomic Data (gget)
Author: plurigrid

byplurigrid

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데이터 과학 및 ML

Provides unified access to over 20 genomic databases for sequence analysis, protein structure prediction, and gene expression queries.

gget is a high-performance toolkit designed to streamline bioinformatics workflows by providing a consistent interface for querying diverse biological databases. It enables researchers to perform BLAST and BLAT searches, download reference genomes, predict protein structures via AlphaFold, and analyze single-cell RNA-seq data directly from the command line or Python environment. By automating data retrieval and formatting from sources like Ensembl, UniProt, and NCBI, gget eliminates the need for manual downloads and complex API handling, making it an essential tool for rapid genomic discovery and computational biology within Claude Code.

주요 기능

01Unified querying across 20+ databases including Ensembl, UniProt, and NCBI

02Automated reference genome downloads and metadata extraction

03Comprehensive gene expression data retrieval from ARCHS4 and CZ CELLxGENE

043D protein structure prediction and visualization with AlphaFold2 integration

05Rapid sequence alignment and analysis using BLAST, BLAT, Muscle, and DIAMOND

068 GitHub stars

사용 사례

01Predicting protein structures and identifying eukaryotic linear motifs for structural biology

02Batch retrieving gene metadata, protein isoforms, and tissue expression for genomic studies

03Identifying unknown sequences through rapid BLAST searches and genomic mapping

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi gget

For use in Claude.ai and ChatGPT

Download Skill