The NHGRI GWAS Catalog, a curated resource of SNP-trait associations

By Danielle Welter, J. MacArthur, Joannella Morales, Tony Burdett, Peggy Hall, Heather Junkins, Alan Klemm, Paul Flicek, Teri Manolio, L. Hindorff and 1 more. 2013

2,838 citations recorded by the source corpus.

The National Human Genome Research Institute (NHGRI) Catalog of Published Genome-Wide Association Studies (GWAS) Catalog provides a publicly available manually curated collection of published GWAS assaying at least 100 000 single-nucleotide polymorphisms (SNPs) and all SNP-trait associations with P <1 × 10−5. The Catalog includes 1751 curated publications of 11 912 SNPs. In addition to the SNP-trait association data, the Catalog also publishes a quarterly diagram of all SNP-trait associations mapped to the SNPs’ chromosomal locations. The Catalog can be accessed via a tabular web interface, via a dynamic visualization on the human karyotype, as a downloadable tab-delimited file and as an OWL knowledge base. This article presents a number of recent improvements to the Catalog, including novel ways for users to interact with the Catalog and changes to the curation infrastructure.

Subfields: Genetics, Molecular Biology

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Citations in the corpus

Knock Knock, Who's There? Membership Inference on Aggregate Location Data (2017, background): “This is relevant in the context of genomic research, where data inherently tied to sensitive information, such as health stats or physical traits, is commonly released in aggregate form for Genome Wide Association Studies (GWAS) [35].”
LDlinkR: An R Package for Rapidly Calculating Linkage Disequilibrium Statistics in Diverse Populations (2020, background): “Genome-wide association studies (GWAS) also apply LD to identify genotype-phenotype associations for a range of disease phenotypes (Welter et al., 2013; Chanock et al., 2014).”
The Post-GWAS Era: From Association to Function. (2018, background): “The GWAS era has been successful in the sense that thousands of loci have been statistically associated with risk for diseases and traits, and a notable number of these loci are well-replicated, suggesting that they are true associations.(11) However, several factors have made it difficult to bridge”
Genome-wide genetic data on ~500,000 UK Biobank participants (2017, methodology): “As a final demonstration of the quality of the directly genotyped and imputed data we conducted a genome-wide association scan for a well-studied [49], and highly”
Polygenic Influence on Educational Attainment: New evidence from The National Longitudinal Study of Adolescent to Adult Health (2015, background): “In the case of human height, a trait measured with high precision, a GWAS of nearly one quarter million individuals recently generated a polygenic score predicting nearly 30% of population variance (Wood et al., 2014).”
RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data (2017, methodology): “As described in our previous study (37), the human disease/trait-associated SNPs were curated from published GWAS data provided by the NHGRI GWAS Catalog (38), Johnson and O’Donnell (39), dbGAP (40) and GAD (41), as well as the SNPs in linkage disequilibrium (LD, r2 ≥ 0.5; Supplementary Table S2) wi”
Gene: a gene-centered information resource at NCBI (2014, methodology): “org/data-curation/structuralvariant-curation/) and c) information from the NHGRI GWAS Catalog (14).”
eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data (2016, background): “The search for genetic factors through genome-wide association studies (GWAS) has identified thousands of replicated SNPs associated with many diseases and other complex phenotypes (Welter et al., 2014).”