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Workshop proceedings: GWAS summary statistics standards and sharing
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 SumSt...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451133/ https://www.ncbi.nlm.nih.gov/pubmed/36082306 http://dx.doi.org/10.1016/j.xgen.2021.100004 |
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author | MacArthur, Jacqueline A.L. Buniello, Annalisa Harris, Laura W. Hayhurst, James McMahon, Aoife Sollis, Elliot Cerezo, Maria Hall, Peggy Lewis, Elizabeth Whetzel, Patricia L. Bahcall, Orli G. Barroso, Inês Carroll, Robert J. Inouye, Michael Manolio, Teri A. Rich, Stephen S. Hindorff, Lucia A. Wiley, Ken Parkinson, Helen |
author_facet | MacArthur, Jacqueline A.L. Buniello, Annalisa Harris, Laura W. Hayhurst, James McMahon, Aoife Sollis, Elliot Cerezo, Maria Hall, Peggy Lewis, Elizabeth Whetzel, Patricia L. Bahcall, Orli G. Barroso, Inês Carroll, Robert J. Inouye, Michael Manolio, Teri A. Rich, Stephen S. Hindorff, Lucia A. Wiley, Ken Parkinson, Helen |
author_sort | MacArthur, Jacqueline A.L. |
collection | PubMed |
description | 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. With the aim of increasing the availability, quality, and utility of GWAS SumStats, the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalog organized a community workshop to address the standards, infrastructure, and incentives required to promote and enable sharing. We evaluated the barriers to SumStats sharing, both technological and sociological, and developed an action plan to address those challenges and ensure that SumStats and study metadata are findable, accessible, interoperable, and reusable (FAIR). We encourage early deposition of datasets in the GWAS Catalog as the recognized central repository. We recommend standard requirements for reporting elements and formats for SumStats and accompanying metadata as guidelines for community standards and a basis for submission to the GWAS Catalog. Finally, we provide recommendations to enable, promote, and incentivize broader data sharing, standards and FAIRness in order to advance genomic medicine. |
format | Online Article Text |
id | pubmed-9451133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94511332022-09-07 Workshop proceedings: GWAS summary statistics standards and sharing MacArthur, Jacqueline A.L. Buniello, Annalisa Harris, Laura W. Hayhurst, James McMahon, Aoife Sollis, Elliot Cerezo, Maria Hall, Peggy Lewis, Elizabeth Whetzel, Patricia L. Bahcall, Orli G. Barroso, Inês Carroll, Robert J. Inouye, Michael Manolio, Teri A. Rich, Stephen S. Hindorff, Lucia A. Wiley, Ken Parkinson, Helen Cell Genom Perspective 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. With the aim of increasing the availability, quality, and utility of GWAS SumStats, the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalog organized a community workshop to address the standards, infrastructure, and incentives required to promote and enable sharing. We evaluated the barriers to SumStats sharing, both technological and sociological, and developed an action plan to address those challenges and ensure that SumStats and study metadata are findable, accessible, interoperable, and reusable (FAIR). We encourage early deposition of datasets in the GWAS Catalog as the recognized central repository. We recommend standard requirements for reporting elements and formats for SumStats and accompanying metadata as guidelines for community standards and a basis for submission to the GWAS Catalog. Finally, we provide recommendations to enable, promote, and incentivize broader data sharing, standards and FAIRness in order to advance genomic medicine. Elsevier 2021-10-13 /pmc/articles/PMC9451133/ /pubmed/36082306 http://dx.doi.org/10.1016/j.xgen.2021.100004 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Perspective MacArthur, Jacqueline A.L. Buniello, Annalisa Harris, Laura W. Hayhurst, James McMahon, Aoife Sollis, Elliot Cerezo, Maria Hall, Peggy Lewis, Elizabeth Whetzel, Patricia L. Bahcall, Orli G. Barroso, Inês Carroll, Robert J. Inouye, Michael Manolio, Teri A. Rich, Stephen S. Hindorff, Lucia A. Wiley, Ken Parkinson, Helen Workshop proceedings: GWAS summary statistics standards and sharing |
title | Workshop proceedings: GWAS summary statistics standards and sharing |
title_full | Workshop proceedings: GWAS summary statistics standards and sharing |
title_fullStr | Workshop proceedings: GWAS summary statistics standards and sharing |
title_full_unstemmed | Workshop proceedings: GWAS summary statistics standards and sharing |
title_short | Workshop proceedings: GWAS summary statistics standards and sharing |
title_sort | workshop proceedings: gwas summary statistics standards and sharing |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451133/ https://www.ncbi.nlm.nih.gov/pubmed/36082306 http://dx.doi.org/10.1016/j.xgen.2021.100004 |
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