Abstract
Genetic association studies have facilitated a remarkable range of discoveries improving our understanding of the underlying biology of diseases, and translation toward new therapeutics. Although large datasets such as UK Biobank can considerably improve the power of these studies, the difficulties of dealing with them are also increasing. One of the main results of the proposed research was to use the power of a large supercomputer to analyze and publish genetic association studies for 778 human traits and diseases, freely available for any researcher. To this end, a web service was developed to allow researchers to freely browse for these associations and compare them between traits. This tool simplifies the work of geneticists, epidemiologists, medical researchers, and pharmaceutical companies when looking for these associations, thus boosting the research process.
Please note that this research has been conducted under application 788 (PI: Albert Tenesa, title: 'Heritability of disease frequency').
The return has been archived under application 4939 to align with the participant identifiers included in the data files. Once downloaded the file extension should be changed to .7z, and extracted using 7zip software.
1 Application
Application ID | Title |
4939 | Estimation of the genetic correlation among human cancers and correlated intermediate traits and identification of pleiotropic cancer loci |
2 Returns
Return ID | App ID | Description | Archive Date |
2422 | 4939 | An atlas of genetic associations in UK Biobank | 21 Sep 2020 |
2501 | 4939 | An atlas of genetic associations in UK Biobank | 19 Oct 2020 |