Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database Profile

General information

URL: https://gnomad.broadinstitute.org/
Full name: Genome Aggregation Database
Description: The Genome Aggregation Database (gnomAD) is a resource developed by an international coalition of investigators, with the goal of aggregating and harmonizing both exome and genome sequencing data from a wide variety of large-scale sequencing projects, and making summary data available for the wider scientific community.
Year founded: 2016
Last update:
Version: v2.1.1 & v3
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: United States
Data type:
DNA
Data object:
Database category:
Major organism:
Keywords:

Contact information

University/Institution: Broad Institute
Address:
City:
Province/State:
Country/Region: United States
Contact name (PI/Team): Genome Aggregation Database Consortium
Contact email (PI/Helpdesk): exomeconsortium@gmail.com

Publications

32461654
The mutational constraint spectrum quantified from variation in 141,456 humans. [PMID: 32461654]
Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, Collins RL, Laricchia KM, Ganna A, Birnbaum DP, Gauthier LD, Brand H, Solomonson M, Watts NA, Rhodes D, Singer-Berk M, England EM, Seaby EG, Kosmicki JA, Walters RK, Tashman K, Farjoun Y, Banks E, Poterba T, Wang A, Seed C, Whiffin N, Chong JX, Samocha KE, Pierce-Hoffman E, Zappala Z, O'Donnell-Luria AH, Minikel EV, Weisburd B, Lek M, Ware JS, Vittal C, Armean IM, Bergelson L, Cibulskis K, Connolly KM, Covarrubias M, Donnelly S, Ferriera S, Gabriel S, Gentry J, Gupta N, Jeandet T, Kaplan D, Llanwarne C, Munshi R, Novod S, Petrillo N, Roazen D, Ruano-Rubio V, Saltzman A, Schleicher M, Soto J, Tibbetts K, Tolonen C, Wade G, Talkowski ME, Genome Aggregation Database Consortium, Neale BM, Daly MJ, MacArthur DG.

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

Nature. 2020:581(7809) | 486 Citations (from Europe PMC, 2021-06-12)

Ranking

All databases:
16/4987 (99.699%)
Raw bio-data:
4/487 (99.384%)
Gene genome and annotation:
8/1343 (99.479%)
Genotype phenotype and variation:
4/700 (99.571%)
16
Total Rank
486
Citations
486
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Record metadata

Created on: 2020-07-06
Curated by:
lin liu [2021-01-21]
Dong Zou [2020-07-06]