GenOMICC release 3
| Depositor | dc.contributor | pairo-castineira, Erola | |
| Funder | dc.contributor.other | BBSRC - Biotechnology and Biological Sciences Research Council | en_UK |
| Funder | dc.contributor.other | MRC - Medical Research Council | en_UK |
| Funder | dc.contributor.other | NIHR - National Institute for Health Research | en_UK |
| Funder | dc.contributor.other | UKRI - UK Research and Innovation | en_UK |
| Funder | dc.contributor.other | Wellcome Trust | en_UK |
| Funder | dc.contributor.other | DHSC - Department of Health and Social Care | en_UK |
| Funder | dc.contributor.other | Sepsis Research (The Fiona Elizabeth Agnew Trust) | |
| Funder | dc.contributor.other | Intensive Care Society | |
| Funder | dc.contributor.other | LifeArc | |
| Funder | dc.contributor.other | Genomics England Ltd | |
| Funder | dc.contributor.other | Illumina Inc | |
| Funder | dc.contributor.other | CRUK - Cancer Research UK | |
| Funder | dc.contributor.other | NHS England | |
| Spatial Coverage | dc.coverage.spatial | UK | en |
| Spatial Coverage | dc.coverage.spatial | UNITED KINGDOM | en |
| Spatial Coverage | dc.coverage.spatial | BR | en |
| Spatial Coverage | dc.coverage.spatial | BRAZIL | en |
| Data Creator | dc.creator | Pairo-Castineira, Erola | |
| Data Creator | dc.creator | Rawlik, Konrad | |
| Data Creator | dc.creator | Baillie, Kenneth | |
| Date Accessioned | dc.date.accessioned | 2022-03-16T17:02:04Z | |
| Date Available | dc.date.available | 2023-04-02T04:15:08Z | |
| Citation | dc.identifier.citation | Pairo-Castineira, Erola; Rawlik, Konrad; Baillie, Kenneth. (2022). GenOMICC release 3, [dataset]. University of Edinburgh. Roslin Institute. https://doi.org/10.7488/ds/3418. | en |
| Persistent Identifier | dc.identifier.uri | https://hdl.handle.net/10283/4376 | |
| Persistent Identifier | dc.identifier.uri | https://doi.org/10.7488/ds/3418 | |
| Dataset Description (abstract) | dc.description.abstract | Here, we provide an updated analysis of the international GenOMICC study comprising a combination of microarray genotype data from 11,325 critically ill cases in the UK (9,279 cases) and Brazil (2,186), combined with other studies recruiting hospitalised patients with a strong focus on severe and critical disease: ISARIC4C (655 cases) and SCOURGE consortium (5,934 cases). We put these new results in context by completing a meta-analysis of the new GenOMICC GWAS results with previously-published data. | en_UK |
| Language | dc.language.iso | eng | en_UK |
| Publisher | dc.publisher | University of Edinburgh. Roslin Institute | en_UK |
| Relation (Is Referenced By) | dc.relation.isreferencedby | https://www.medrxiv.org/content/10.1101/2022.03.07.22271833v1 | en_UK |
| Relation (Is Referenced By) | dc.relation.isreferencedby | GWAS and meta-analysis identifies multiple new genetic mechanisms underlying severe Covid-19. Erola Pairo-Castineira, Konrad Rawlik, Lucija Klaric, Andy Law, Sara Clohisey Hendry, J. Kenneth Baillie medRxiv 2022.03.07.22271833; doi: https://doi.org/10.1101/2022.03.07.22271833 This article is a preprint and has not been certified by peer review. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice. | en_UK |
| Rights | dc.rights | These latest unpublished results for this data release are shared with the global community before publication in order to accelerate discovery. We share our results on the understanding that no investigator should publish any work derived from these results without express agreement of the GenOMICC Investigators. | en |
| Subject | dc.subject | GenOMICC | en_UK |
| Subject | dc.subject | GWAS | en_UK |
| Subject | dc.subject | COVID-19 | en_UK |
| Subject | dc.subject | Summary Statistics | en_UK |
| Subject Classification | dc.subject.classification | Biological Sciences | en_UK |
| Title | dc.title | GenOMICC release 3 | en_UK |
| Alternative Title | dc.title.alternative | GWAS summary statistics GenOMICC meta-analysis for hospitalised and critically ill datasets | en_UK |
| Type | dc.type | dataset | en_UK |
zip file MD5 Checksum:
557a569db47c54f7f519c7a1393c9601
Files in this item
This item appears in the following Collection(s)
-
COVID-19 Collection
Cross discipline datasets relating to COVID-19 -
Genetics and Genomics
