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Training & Related resources

  1. GWAS Catalog training materials

  2. Publications

  3. Useful resources

  4. Community workshops

GWAS Catalog training materials​

EBI Train online​

New to the Catalog? Start here with GWAS Catalog - Exploring SNP-trait associations, an easily accessible interactive tutorial on the full range of features the GWAS Catalog has to offer.

Training videos​

Recorded webinars are available to guide you through different aspects of the Catalog:

Earlier webinars are also available:

In-person training materials​

Training materials from in-person training workshops held by the GWAS Catalog team are available on Github and our FTP server. If you would like to make use of these slides, please cite the GWAS Catalog as detailed on the About page.

Publications​

GWAS Catalog publications​

Current GWAS Catalog citation: Cerezo et al, 2025 https://doi.org/10.1093/nar/gkae1070 Nucleic Acids Research, Volume 53, Issue D1, Pages D998–D1005

Older resource update papers:​

Sollis et al, 2023 https://doi.org/10.1093/nar/gkac1010. Nucleic Acids Research 51(D1):D977-D985

Buniello, MacArthur et al, 2019 https://doi.org/10.1093/nar/gky1120. Nucleic Acids Research, 2019, Vol. 47 (Database issue): D1005-D1012.

MacArthur et al, 2017 https://doi.org/10.1093/nar/gkw1133. Nucleic Acids Research, Vol. 45 (Database issue): D896-D901.

Welter D et al, 2014 https://doi.org/10.1093/nar/gkt1229. Nucleic Acids Research, Vol. 42 (Database issue): D1001-D1006.

Other GWAS Catalog papers:​

Harris et al, 2024 Genome-wide association testing beyond SNPs. Nature Reviews Genetics. 2024 Oct 7. Epub ahead of print.

MacArthur et al, 2021 Workshop proceedings: GWAS Catalog standards and sharing. Cell Genomics Vol. 1, Issue 1, 100004.

McMahon et al, 2021 Sequencing-based genome-wide association studies reporting standards. Cell Genomics Vol. 1, issue 1, 100005.

Morales et al, 2017 A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog. Genome Biology, 19:21.

Hindorff LA, et al 2009 Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA, 2009, 106, 9362–9367.

Papers with GWAS Catalog contribution:​

Costanzo et al, 2025 Realizing the promise of genome-wide association studies for effector gene prediction, Nature Genetics, Volume 57:1578–1587, May 2025.

Matentzoglu et al, 2025 The Unified Phenotype Ontology : a framework for cross-species integrative phenomics, Genetics, Volume 229, Issue 3, March 2025

Lambert, Wingfield et al, 2024. Enhancing the Polygenic Score Catalog with tools for score calculation and ancestry normalization. Nature Genetics. 56(10):1989-1994, Oct 2024.

Stefancik et al, 2023 The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences. Mammalian Genome 34, 364–378.

Lambert et al, 2021 The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation. Nature Genetics volume 53, pages420–425.

Lee K et al, 2018 Scaling up data curation using deep learning: An application to literature triage in genomic variation resources. PLoS Computational Biology 14(8):e1006390.

Other background reading​

Uffelmann et al, 2021 Genome-wide association studies. Nat Rev Methods Primers 1, 59.

A beginners guide to GWAS (2016)

What is an Ontology? (2010)

Abdellaoui et al, 2023. 15 years of GWAS discovery: Realizing the promise. Am J Hum Genet. 2023 Feb 2;110(2):179-194.

Visscher et al, 2017 10 Years of GWAS Discovery: Biology, Function and Translation AJHG Volume 101, Issue 1, 6 July 2017, Pages 5-22

Manolio, 2010 Genomewide Association Studies and assessment of the risk of disease NEJM 363:166-176

News posts​

Trait annotation in the GWAS Catalog (2021): a discussion of how traits are annotated in the GWAS Catalog, focussing on improved background trait annotation.

Sharing is caring: why we need more freely available cancer GWAS summary statistics (2021): a blog post calling for more freely available cancer GWAS summary statistics.

Ten years of the GWAS Catalog – Past, present and future(2018): 10th Anniversary blog post highlighting the links between the GWAS Catalog and Ensembl.

Everything you need to know about the new GWAS Catalog (2018): a blog post describing the collaboration between the GWAS Catalog and Open Targets.

Or see the full index.

Useful resources​

Tools & data services​

gwasrapiddan R package to query, download and wrangle GWAS Catalog data
pandasgwasA Python package for retrieval of GWAS Catalog data
Variant Effect Predictor (VEP)Determines the effect of variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions
PhenoscannerTool to facilitate “phenome scans”, the cross-referencing of genetic variants with a broad range of phenotypes, using a range of data sources including GWAS, eQTL and metabolite data
HuGE NavigatorKnowledge base in human genome epidemiology, including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions
Phenotype-Genotype IntegratorMerges GWAS Catalog Data with other NCBI databases to facilitate prioritisation of GWAS hits for follow-up
PGS CatalogAn open database of polygenic scores and the relevant metadata required for accurate application and evaluation
Open Targets PlatformPlatform for the identification of drug targets using multiple data types including GWAS
Target Illumination GWAS Analytics (TIGA)Resource for drug target illumination by scoring and ranking protein-coding genes associated with traits from GWAS
LocusZoomA suite of software for creating regional association plots from GWAS data
Elixir Tools and Data Services RegistryA registry of GWAS-related resources and tools
OMICStoolsSearchable database of GWAS and other bioinformatics tools
PharosPharos is the user interface to the Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) program
GWAS Diversity MonitorInteractive dashboard monitoring the diversity of participants across all published GWAS

Resources used within the GWAS Catalog​

For more information on how we use these resources, see our Methods page.

Experimental Factor Ontology (EFO)The ontology used for trait mapping in the GWAS Catalog
Ensembl Genome BrowserGenome browser and data for vertebrate genomes, used in our variant mapping pipeline. Ensembl annotates genes, computes multiple alignments, predicts regulatory function and collects disease data
PubMedLiterature search and citation annotation
EuropePMCLiterature search and citation annotation
CIA FactbookA rich source of population demographic data, used by curators
NCBIData used for variant mapping in older versions of the Catalog

Genome and phenome resources​

1000 GenomesThe largest public reference catalogue of worldwide human variation and genotype data
International HapMap ProjectThe first public catalogue of human variation data, now superseded by 1000Genomes
UCSC Genome BrowserGenome browser to interactively visualize genomic data
PhenX toolkitConsensus measures of Phenotypes and eXposures
dbSNPDatabase of human single nucleotide polymorphisms
National Centre for Biotechnology InformationProvides wide range of resources including Entrez gene, GenBank, PubMed and ClinVar

Sources of summary statistics​

Summary statistics are available via the GWAS Catalog where possible. Find additional sources of summary statistics here.

Community workshops​

Materials from our community workshop on standards and infrastructure for predicted effector gene lists, a collaboration between the GWAS Catalog, HuGEAMP Knowledge Portal Network and Open Targets, are available online.

Materials from our community workshop on GWAS summary statistics standards and sharing, held in June 2020 to address the standards, infrastructure and incentives required to promote and enable broader sharing of data, are available here and are published as MacArthur et al, 2021 Workshop proceedings: GWAS Catalog standards and sharing, Cell Genomics 1(1).