What databases can gget access?

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

Does this skill support sequence alignment?

Yes, it supports multiple alignment methods including BLAST, BLAT (UCSC), Muscle5, and local protein alignment via DIAMOND.

Is gget available for both Python and CLI?

Yes, gget functions as both a command-line interface tool and a Python package, returning data in JSON, CSV, or DataFrame formats.

Can I use gget for protein structure prediction?

Yes, gget includes a module for AlphaFold2 that allows for 3D protein structure prediction directly from amino acid sequences.

How does gget handle large datasets?

gget is designed for speed and includes specific flags like --super5 for Muscle or --sensitivity for DIAMOND to optimize for larger datasets.

Bioinformatics & Genomic Data (gget)

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

byricable

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Ciencia de Datos y ML

Provides a unified interface for rapid bioinformatics queries across 20+ genomic databases including Ensembl, AlphaFold, and NCBI.

Acerca de

gget is a comprehensive toolkit designed to streamline genomic research by providing a consistent interface for querying biological databases. It enables developers and scientists to perform BLAST searches, retrieve reference genomes, predict protein structures using AlphaFold, and analyze gene expression data without switching between disparate web portals or complex API implementations. This skill is particularly useful for automating sequence analysis workflows, conducting large-scale gene metadata retrieval, and integrating protein structural data directly into computational biology pipelines.

Características Principales

Single-cell RNA-seq and tissue expression analysis via CELLxGENE and ARCHS4
Unified access to 20+ genomic databases like Ensembl, UniProt, and NCBI
Protein structure prediction via AlphaFold2 and PDB metadata retrieval
1 GitHub stars
Rapid sequence alignment with BLAST, BLAT, and Muscle5
Reference genome downloading and advanced gene metadata searching

Casos de Uso

Automating the retrieval of FASTA sequences and reference genomes for specific species
Mapping gene lists to expression profiles across different tissues and cell types
Integrating protein structure prediction and linear motif analysis into drug discovery workflows

Acerca de

Características Principales

Single-cell RNA-seq and tissue expression analysis via CELLxGENE and ARCHS4
Unified access to 20+ genomic databases like Ensembl, UniProt, and NCBI
Protein structure prediction via AlphaFold2 and PDB metadata retrieval
1 GitHub stars
Rapid sequence alignment with BLAST, BLAT, and Muscle5
Reference genome downloading and advanced gene metadata searching

Casos de Uso

Automating the retrieval of FASTA sequences and reference genomes for specific species
Mapping gene lists to expression profiles across different tissues and cell types
Integrating protein structure prediction and linear motif analysis into drug discovery workflows