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Shared Genomics: High Performance Computing for distributed insights in genomic medical research

机译：共享基因组学：基因组医学研究分布式见解的高性能计算

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摘要

The study of the genetics of diseases is entering a new era. Increasingly, genome-wide association studies are being used to identify positions within the human genome that have a link with a disease condition. The number of genomic locations studied means that High Performance Computing (HPC) solutions will have to increasingly be used in the statistical analysis of these data sets. Understanding the biomedical implications of the statistical analysis will also require heavy use of bioinformatics annotation tools. In this paper we report the outcome of developing HPC statistical genetics analysis codes for use by clinical researchers. Statistical results are automatically annotated with relevant biological information by calling multiple web-services orchestrated via pre-existing scientific workflows. Access to the HPC codes and bioinformatics annotation processes is via a client Workbench which hides as much as possible from the user the HPC infrastructure and bioinformatics annotation processes, whilst aiding the exchange of ideas and results between stakeholders.
机译：对疾病遗传学的研究正在进入一个新的时代。越来越多地，基因组 - 范围的协会研究用于识别人类基因组内具有疾病状况的联系的位置。所研究的基因组位置的数量意味着高性能计算（HPC）解决方案必须越来越多地用于这些数据集的统计分析中。了解统计分析的生物医学意义还将需要大量使用生物信息学注释工具。在本文中，我们报告了临床研究人员使用的HPC统计遗传分析码的结果。统计结果通过通过预先存在的科学工作流程调用多个Web-Service来自动注释相关的生物信息。访问HPC码和生物信息学的注释过程是通过客户工作台从用户身份隐藏的支持HPC基础设施和生物信息学注释过程，同时助攻在利益相关者之间的思想和结果交换。

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