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

机译:easyGWAS:基于云的平台可比较基因组范围的关联研究结果

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摘要

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 (). The systematic comparison of results obtained from of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple are the ability to replicate 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.
机译:众多物种高质量基因型的可用性不断增长,这使得研究人员能够使用全基因组关联研究以前所未有的详细程度探索复杂表型的潜在遗传结构。从不同特征获得的结果的系统比较开辟了新的可能性,包括对多效性效应的分析。多重集成带来的其他优势是能够复制信号并提高统计能力,以通过荟萃分析检测此类信号。为了简化GWAS结果的简单比较,我们提出了easyGWAS,这是一种功能强大,与物种无关的在线资源,用于计算,存储,共享,注释和比较GWAS。 easyGWAS工具支持多种物种,上传私人基因型数据和现有GWAS的摘要统计信息,以及在交互式和用户友好界面中比较不同实验和数据集的GWAS结果的高级方法。 easyGWAS还是GWAS数据和摘要统计信息的公共数据存储库,已经包含了来自多个主要GWAS的已发布数据和结果。我们通过使用开花和生长相关性状的模式生物拟南芥的案例研究证明了easyGWAS的潜力。

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