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学術論文

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies

MPS-Authors

Grimm,  Dominik G.
Max Planck Institute for Developmental Biology, Max Planck Society;
Max Planck Institute for Intelligent Systems, Max Planck Society;
Zentrum für Bioinformatik, Eberhard Karls Universität, Tübingen;
Department for Biosystems Science and Engineering, ETH Zürich;
Swiss Institute of Bioinformatics, Basel;

Salome,  Patrice A.
Max Planck Institute for Developmental Biology, Max Planck Society;

Kleeberger,  Stefan
Max Planck Institute for Developmental Biology, Max Planck Society;
Max Planck Institute for Intelligent Systems, Max Planck Society;

Greshake,  Bastian
Max Planck Institute for Developmental Biology, Max Planck Society;
Max Planck Institute for Intelligent Systems, Max Planck Society;

Zhu,  Wangsheng
Max Planck Institute for Developmental Biology, Max Planck Society;

Liu,  Chang
Max Planck Institute for Developmental Biology, Max Planck Society;

Lippert,  Christoph
Max Planck Institute for Developmental Biology, Max Planck Society;
Max Planck Institute for Intelligent Systems, Max Planck Society;

Stegle,  Oliver
Max Planck Institute for Developmental Biology, Max Planck Society;
Max Planck Institute for Intelligent Systems, Max Planck Society;

Schoelkopf,  Bernhard
Max Planck Institute for Intelligent Systems, Max Planck Society;

Weigel,  Detlef
Max Planck Institute for Developmental Biology, Max Planck Society;

Borgwardt,  Karsten M.
Max Planck Institute for Developmental Biology, Max Planck Society;
Max Planck Institute for Intelligent Systems, Max Planck Society;
Zentrum für Bioinformatik, Eberhard Karls Universität, Tübingen;
Department for Biosystems Science and Engineering, ETH Zürich;
Swiss Institute of Bioinformatics, Basel;

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引用

Grimm, D. G., Roqueiro, D., Salome, P. A., Kleeberger, S., Greshake, B., Zhu, W., Liu, C., Lippert, C., Stegle, O., Schoelkopf, B., Weigel, D., & Borgwardt, K. M. (2017). easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies. Plant Cell, 29(1), 5-19. doi:10.1105/tpc.16.00551.


引用: http://hdl.handle.net/21.11116/0000-0002-04A9-B
要旨
The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana, using flowering and growth-related traits.