Does gget support protein structure prediction?

Yes, gget includes a module for AlphaFold2 that allows for both monomer and multimer protein structure prediction directly from the command line or Python.

How does gget handle external database updates?

gget modules are automatically tested on a biweekly basis and updated whenever external database structures change to ensure continuous reliability for your research.

Is gget available for both CLI and Python?

Absolutely. All gget modules are designed to work seamlessly as both command-line tools and Python functions, making them easy to integrate into scripts.

Can I use gget for single-cell RNA-seq data?

Yes, the gget cellxgene module allows you to query the CZ CELLxGENE Discover Census for large-scale single-cell data, returning metadata or AnnData objects.

What databases can gget access?

gget provides access to over 20 databases including Ensembl, UniProt, NCBI, RCSB PDB, AlphaFold, ARCHS4, and CZ CELLxGENE.

Bioinformatics Toolkit (gget)

Name: Bioinformatics Toolkit (gget)
Author: ovachiever

byovachiever

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数据科学与机器学习

Accesses 20+ genomic databases for rapid bioinformatics queries, sequence analysis, and protein structure prediction.

关于

gget is a high-performance command-line and Python toolkit designed for bioinformaticians and researchers to efficiently query genomic data across more than 20 major databases. It streamlines complex workflows by providing unified access to reference genomes, BLAST searches, AlphaFold protein structure predictions, and single-cell RNA-seq data from sources like Ensembl, UniProt, and CZ CELLxGENE. Whether used for rapid gene metadata retrieval or heavy-duty sequence alignment, gget ensures reliability through biweekly automated testing against evolving database structures, making it an essential tool for automated biological data analysis.

主要功能

Rapid BLAST and BLAT sequence alignment and genomic mapping
Support for single-cell RNA-seq data and gene correlation analysis via ARCHS4
Automated retrieval of reference genomes, sequences, and gene metadata
Unified access to 20+ genomic databases including Ensembl, UniProt, and NCBI
15 GitHub stars
Integrated protein structure prediction using AlphaFold2 and PDB data

使用场景

Predicting 3D protein structures and linear motifs for novel sequences
Analyzing gene expression correlations and tissue-specific patterns across species
Retrieving amino acid sequences and metadata for large lists of Ensembl IDs

关于

主要功能

Rapid BLAST and BLAT sequence alignment and genomic mapping
Support for single-cell RNA-seq data and gene correlation analysis via ARCHS4
Automated retrieval of reference genomes, sequences, and gene metadata
Unified access to 20+ genomic databases including Ensembl, UniProt, and NCBI
15 GitHub stars
Integrated protein structure prediction using AlphaFold2 and PDB data

使用场景

Predicting 3D protein structures and linear motifs for novel sequences
Analyzing gene expression correlations and tissue-specific patterns across species
Retrieving amino acid sequences and metadata for large lists of Ensembl IDs