Publications by authors named "Peggy Hall"

The NHGRI-EBI GWAS Catalog serves as a vital resource for the genetic research community, providing access to the most comprehensive database of human GWAS results. Currently, it contains close to 7 000 publications for >15 000 traits, from which more than 625 000 lead associations have been curated. Additionally, 85 000 full genome-wide summary statistics datasets-containing association data for all variants in the analysis-are available for downstream analyses such as meta-analysis, fine-mapping, Mendelian randomisation or development of polygenic risk scores.

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The NHGRI-EBI GWAS Catalog serves as a vital resource for the genetic research community, providing access to the most comprehensive database of human GWAS results. Currently, it contains close to 7,000 publications for more than 15,000 traits, from which more than 625,000 lead associations have been curated. Additionally, 85,000 full genome-wide summary statistics datasets - containing association data for all variants in the analysis - are available for downstream analyses such as meta-analysis, fine-mapping, Mendelian randomisation or development of polygenic risk scores.

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Genome-wide association studies (GWASs) have enabled robust mapping of complex traits in humans. The open sharing of GWAS summary statistics (SumStats) is essential in facilitating the larger meta-analyses needed for increased power in resolving the genetic basis of disease. However, most GWAS SumStats are not readily accessible because of limited sharing and a lack of defined standards.

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Article Synopsis
  • Genome sequencing is now an effective method for conducting genome-wide association studies (GWASs), allowing the analysis of a wider range of genetic variations, including rare ones.
  • A study of 167 GWAS publications from 2014 to 2020 revealed issues like inconsistent terminology and incomplete dataset reporting, especially for variants in aggregate tests, despite 81% including tests for multiple variants.
  • The authors call for improved reporting standards and data sharing to enhance the findability and accessibility of sequencing-based data, suggesting the adoption of standard terminology (seqGWAS) and better practices for single and aggregate variant analysis.
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Article Synopsis
  • The GWAS Catalog is a comprehensive resource for published genome-wide association studies, helping researchers identify disease-related genetic variants and develop new therapies.
  • The Catalog now includes data from targeted and exome arrays, with over 71000 associations from nearly 5700 studies, updating its content to support advanced research.
  • Recent enhancements include a RESTful API for easier data access, an upgraded user interface, and standardized formats for sharing summary statistics, significantly improving usability for the approximately 90,000 users who accessed the site in the last year.
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The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog.

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The NHGRI-EBI GWAS Catalog has provided data from published genome-wide association studies since 2008. In 2015, the database was redesigned and relocated to EMBL-EBI. The new infrastructure includes a new graphical user interface (www.

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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.

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The authors present a case of severe meningoencephalitis with cryptococcomas and hydrocephalus due to Cryptococcus gattii of the molecular type VGI in an otherwise healthy man native to Southwest Georgia without any history of travel. Clinicians need to be aware of this fungal emerging pathogen in the Southern United States.

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