The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource.
The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource.
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DOI：
10.1093/nar/gkac1010
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发表时间：
2023-01-06
影响因子：
14.9
通讯作者：
Harris, Laura W.
中科院分区：
文献类型：
--
作者：
Sollis, Elliot;Mosaku, Abayomi;Abid, Ala;Buniello, Annalisa;Cerezo, Maria;Gil, Laurent;Groza, Tudor;Gunes, Osman;Hall, Peggy;Hayhurst, James;Ibrahim, Arwa;Ji, Yue;John, Sajo;Lewis, Elizabeth;MacArthur, Jacqueline A. L.;McMahon, Aoife;Osumi-Sutherland, David;Panoutsopoulou, Kalliope;Pendlington, Zoe;Ramachandran, Santhi;Stefancsik, Ray;Stewart, Jonathan;Whetzel, Patricia;Wilson, Robert;Hindorff, Lucia;Cunningham, Fiona;Lambert, Samuel A.;Inouye, Michael;Parkinson, Helen;Harris, Laura W.
NHGRI-EBI GWAS 目录 (www.ebi.ac.uk/gwas) 是一个 FAIR 知识库，每年向来自学术研究、医疗保健和行业的超过 200 000 名用户提供详细、结构化、标准化和可互操作的全基因组关联研究 (GWAS) 数据。该目录包含超过 45 000 个已发布的 GWAS（涵盖超过 5000 个人类特征）的变异-性状关联和支持元数据，以及超过 40 000 个完整的 P 值汇总统计数据集。内容是从出版物中策划的，或者是通过作者通过新的提交门户和验证工具提交出版前摘要统计数据来获取的。近年来，GWAS 数据量大幅增加。我们更新了我们的软件来应对这一扩展挑战，并能够快速发布提交的汇总统计数据。存储库的范围已扩大到包括社区高度感兴趣的其他数据类型，包括基于测序的 GWAS、基于基因的分析和拷贝数变异分析。社区外展增加了代表性不足特征的共享数据集的数量，例如癌症，我们继续致力于提高人们对 GWAS 中缺乏人口多样性的认识。通过与其他资源（包括多基因评分目录和国际小鼠表型联盟）的链接、GWAS 性状注释的完善以及 GWAS 数据标准格式的开发，目录的互操作性得到了增强。
The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry. The Catalog contains variant-trait associations and supporting metadata for >45 000 published GWAS across >5000 human traits, and >40 000 full P-value summary statistics datasets. Content is curated from publications or acquired via author submission of prepublication summary statistics through a new submission portal and validation tool. GWAS data volume has vastly increased in recent years. We have updated our software to meet this scaling challenge and to enable rapid release of submitted summary statistics. The scope of the repository has expanded to include additional data types of high interest to the community, including sequencing-based GWAS, gene-based analyses and copy number variation analyses. Community outreach has increased the number of shared datasets from under-represented traits, e.g. cancer, and we continue to contribute to awareness of the lack of population diversity in GWAS. Interoperability of the Catalog has been enhanced through links to other resources including the Polygenic Score Catalog and the International Mouse Phenotyping Consortium, refinements to GWAS trait annotation, and the development of a standard format for GWAS data.
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影响因子：
14.9
作者：
Ghoussaini M;Mountjoy E;Carmona M;Peat G;Schmidt EM;Hercules A;Fumis L;Miranda A;Carvalho-Silva D;Buniello A;Burdett T;Hayhurst J;Baker J;Ferrer J;Gonzalez-Uriarte A;Jupp S;Karim MA;Koscielny G;Machlitt-Northen S;Malangone C;Pendlington ZM;Roncaglia P;Suveges D;Wright D;Vrousgou O;Papa E;Parkinson H;MacArthur JAL;Todd JA;Barrett JC;Schwartzentruber J;Hulcoop DG;Ochoa D;McDonagh EM;Dunham I
通讯作者：
Dunham I
DOI：
10.1016/j.xgen.2022.100167
发表时间：
2022-08-10
期刊：
CELL GENOMICS
影响因子：
--
作者：
Fitzgerald, Tomas;Birney, Ewan
通讯作者：
Birney, Ewan
影响因子：
9.8
作者：
通讯作者：
--
影响因子：
14.9
作者：
Buniello, Annalisa;MacArthur, Jacqueline A. L.;Parkinson, Helen
通讯作者：
Parkinson, Helen
影响因子：
5.8
作者：
Kamat, Mihir A.;Blackshaw, James A.;Staley, James R.
通讯作者：
Staley, James R.