When should I use gget vs Biopython?

gget is optimized for rapid, user-friendly queries and quick BLAST searches. For highly advanced batch processing or custom low-level file manipulation, Biopython remains the recommended alternative.

Does this skill support sequence alignment?

Yes, it supports several high-performance alignment methods including BLAST, BLAT, Muscle5, and DIAMOND for both local and global alignments.

What databases can gget access through Claude Code?

gget provides unified access to over 20 databases including Ensembl, UniProt, NCBI, AlphaFold, ARCHS4, Enrichr, and CELLxGENE for comprehensive biological research.

Can I use gget for protein structure prediction?

Yes, gget includes a module for AlphaFold2 that allows you to predict 3D protein structures and multimers directly from amino acid sequences.

Is gget suitable for single-cell RNA-seq data?

Absolutely. gget integrates with the CZ CELLxGENE Discover Census to query and download metadata or expression data from massive single-cell datasets.

Bioinformatics & Genomic Data (gget)

Name: Bioinformatics & Genomic Data (gget)
Author: K-Dense-AI

byK-Dense-AI

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3,718

Data Science & ML

Simplifies bioinformatics workflows by providing unified access to over 20 genomic and proteomic databases for sequence analysis and protein modeling.

About

gget is a comprehensive toolkit designed for rapid bioinformatics queries and data retrieval directly within development environments. It bridges the gap between raw genomic data and analysis by offering a consistent interface for querying gene information from Ensembl and UniProt, performing BLAST/BLAT sequence searches, and even predicting 3D protein structures via AlphaFold. Whether you need to download reference genomes, analyze single-cell RNA-seq data from CELLxGENE, or perform multiple sequence alignments, gget provides a streamlined, programmatically accessible way to integrate high-quality scientific data into your computational biology workflows.

Key Features

Integrated BLAST, BLAT, and DIAMOND sequence alignment tools
Unified access to 20+ genomic databases including Ensembl, UniProt, and NCBI
Automated 3D protein structure prediction and visualization using AlphaFold2
3,718 GitHub stars
Native support for both command-line execution and Python-based data analysis
High-performance retrieval of single-cell RNA-seq data and tissue expression patterns

Use Cases

Performing genomic sequence alignments and identifying conserved motifs in protein sequences
Predicting protein folding and multimer structures for structural biology research
Rapidly fetching gene metadata, sequences, and isoforms for specific Ensembl or UniProt IDs

About

Key Features

Integrated BLAST, BLAT, and DIAMOND sequence alignment tools
Unified access to 20+ genomic databases including Ensembl, UniProt, and NCBI
Automated 3D protein structure prediction and visualization using AlphaFold2
3,718 GitHub stars
Native support for both command-line execution and Python-based data analysis
High-performance retrieval of single-cell RNA-seq data and tissue expression patterns

Use Cases

Performing genomic sequence alignments and identifying conserved motifs in protein sequences
Predicting protein folding and multimer structures for structural biology research
Rapidly fetching gene metadata, sequences, and isoforms for specific Ensembl or UniProt IDs