gget

gget is a free, open-source command-line tool and Python package for querying genomic databases. It was developed by Laura Luebbert in the Pachter Lab and is part of the scverse project, fiscally sponsored by NumFOCUS. Its latest listed release is v0.30.8.

What It Is

gget is a collection of separate but interoperable modules, each designed to handle one type of database query in a single line of code. It can be used from the command line, from Python in Jupyter Lab or Google Colab, and from R through reticulate. Typical inputs are gene names, Ensembl IDs, nucleotide or amino acid sequences, PDB IDs, and gene lists. Outputs include reference genome links, sequences, alignments, annotations, expression data, and protein structures.

Modules and Workflows

The modules cover several areas of genomic and proteomic lookup:

• Gene and sequence lookup: gget ref fetches Ensembl reference genomes, gget search finds Ensembl IDs, gget info retrieves annotations for an Ensembl ID, and gget seq fetches nucleotide or amino acid sequences.
• Sequence analysis: gget blast, blat, muscle, and diamond handle BLAST searches, genomic location lookup, multiple sequence alignment, and alignment to a reference.
• Expression and disease context: archs4, 8cube, bgee, cbio, cosmic, opentargets, and enrichr cover tissue expression, orthologs, cancer data, disease and drug associations, and enrichment analysis.
• Structure and motifs: gget pdb fetches Protein Data Bank data, gget elm finds eukaryotic linear motifs, and gget g2p links genes and proteins to residue-level annotations.
• Data retrieval: gget cellxgene returns single-cell RNA-seq count matrices in AnnData format, and gget virus filters and fetches viral sequences with metadata from NCBI Virus.
• Sequence editing: gget mutate changes nucleotide sequences based on specified mutations.

Setup Path

Install with pip or uv, or from source via git. Some modules, such as elm and cellxgene, need a one-time gget setup step. The documentation notes that the queried databases change over time, and that modules are automatically tested twice weekly and updated as needed. The project is BSD 2-Clause licensed and asks users to cite the 2023 Bioinformatics paper.