Python arguments are equivalent to long-option arguments (--arg), unless otherwise specified. Flags are True/False arguments in Python. The manual for any gget tool can be called from the command-line using the -h --help flag.

gget info 💡

Fetch extensive gene and transcript metadata from Ensembl, UniProt, and NCBI using Ensembl IDs.
Return format: JSON (command-line) or data frame/CSV (Python).

Positional argument
ens_ids
One or more Ensembl IDs (WormBase and Flybase IDs are also supported).
NOTE: Providing a list of more than 1,000 Ensembl IDs at once might result in a server error (to process more than 1,000 IDs, split the list of IDs into chunks of 1,000 IDs and run these separately).

Optional arguments
-o --out
Path to the file the results will be saved in, e.g. path/to/directory/results.csv (or .json). Default: Standard out.
Python: save=True will save the output in the current working directory.

Flags
-n --ncbi
TURN OFF results from NCBI.
Python: ncbi=False prevents data retrieval from NCBI (default: True).

-u --uniprot
TURN OFF results from UniProt.
Python: uniprot=False prevents data retrieval from UniProt (default: True).

-pdb --pdb
INCLUDE PDB IDs in output (might increase runtime).
Python: pdb=True includes PDB IDs in the results (default: False).

-csv --csv
Command-line only. Returns results in CSV format.
Python: Use json=True to return output in JSON format.

-q --quiet
Command-line only. Prevents progress information from being displayed.
Python: Use verbose=False to prevent progress information from being displayed.

wrap_text
Python only. wrap_text=True displays data frame with wrapped text for easy reading (default: False).

Example

gget info ENSG00000034713 ENSG00000104853 ENSG00000170296

# Python
gget.info(["ENSG00000034713", "ENSG00000104853", "ENSG00000170296"])

→ Returns extensive information about each requested Ensembl ID:

	uniprot_id	ncbi_gene_id	primary_gene_name	synonyms	protein_names	ensembl_description	uniprot_description	ncbi_description	biotype	canonical_transcript	...
ENSG00000034713	P60520	11345	GABARAPL2	[ATG8, ATG8C, FLC3A, GABARAPL2, GATE-16, GATE16, GEF-2, GEF2]	Gamma-aminobutyric acid receptor-associated protein like 2 (GABA(A) receptor-associated protein-like 2)...	GABA type A receptor associated protein like 2 [Source:HGNC Symbol;Acc:HGNC:13291]	FUNCTION: Ubiquitin-like modifier involved in intra- Golgi traffic (By similarity). Modulates intra-Golgi transport through coupling between NSF activity and ...	Enables ubiquitin protein ligase binding activity. Involved in negative regulation of proteasomal protein catabolic process and protein...	protein_coding	ENST00000037243.7	...
. . .	. . .	. . .	. . .	. . .	. . .	. . .	. . .	. . .	. . .	. . .	...

More examples

References

If you use gget info in a publication, please cite the following articles:

Luebbert, L., & Pachter, L. (2023). Efficient querying of genomic reference databases with gget. Bioinformatics. https://doi.org/10.1093/bioinformatics/btac836
Martin FJ, Amode MR, Aneja A, Austine-Orimoloye O, Azov AG, Barnes I, Becker A, Bennett R, Berry A, Bhai J, Bhurji SK, Bignell A, Boddu S, Branco Lins PR, Brooks L, Ramaraju SB, Charkhchi M, Cockburn A, Da Rin Fiorretto L, Davidson C, Dodiya K, Donaldson S, El Houdaigui B, El Naboulsi T, Fatima R, Giron CG, Genez T, Ghattaoraya GS, Martinez JG, Guijarro C, Hardy M, Hollis Z, Hourlier T, Hunt T, Kay M, Kaykala V, Le T, Lemos D, Marques-Coelho D, Marugán JC, Merino GA, Mirabueno LP, Mushtaq A, Hossain SN, Ogeh DN, Sakthivel MP, Parker A, Perry M, Piližota I, Prosovetskaia I, Pérez-Silva JG, Salam AIA, Saraiva-Agostinho N, Schuilenburg H, Sheppard D, Sinha S, Sipos B, Stark W, Steed E, Sukumaran R, Sumathipala D, Suner MM, Surapaneni L, Sutinen K, Szpak M, Tricomi FF, Urbina-Gómez D, Veidenberg A, Walsh TA, Walts B, Wass E, Willhoft N, Allen J, Alvarez-Jarreta J, Chakiachvili M, Flint B, Giorgetti S, Haggerty L, Ilsley GR, Loveland JE, Moore B, Mudge JM, Tate J, Thybert D, Trevanion SJ, Winterbottom A, Frankish A, Hunt SE, Ruffier M, Cunningham F, Dyer S, Finn RD, Howe KL, Harrison PW, Yates AD, Flicek P. Ensembl 2023. Nucleic Acids Res. 2023 Jan 6;51(D1):D933-D941. doi: 10.1093/nar/gkac958. PMID: 36318249; PMCID: PMC9825606.
Sayers EW, Beck J, Bolton EE, Brister JR, Chan J, Comeau DC, Connor R, DiCuccio M, Farrell CM, Feldgarden M, Fine AM, Funk K, Hatcher E, Hoeppner M, Kane M, Kannan S, Katz KS, Kelly C, Klimke W, Kim S, Kimchi A, Landrum M, Lathrop S, Lu Z, Malheiro A, Marchler-Bauer A, Murphy TD, Phan L, Prasad AB, Pujar S, Sawyer A, Schmieder E, Schneider VA, Schoch CL, Sharma S, Thibaud-Nissen F, Trawick BW, Venkatapathi T, Wang J, Pruitt KD, Sherry ST. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2024 Jan 5;52(D1):D33-D43. doi: 10.1093/nar/gkad1044. PMID: 37994677; PMCID: PMC10767890.
The UniProt Consortium , UniProt: the Universal Protein Knowledgebase in 2023, Nucleic Acids Research, Volume 51, Issue D1, 6 January 2023, Pages D523–D531, https://doi.org/10.1093/nar/gkac1052