Analysing Cancer Genomics in the Elastic Cloud

Christopher Smowton, Crispin J. Miller, W. Xing, Andoena Balla, D. Antoniades, G. Pallis, M. Dikaiakos
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引用次数: 3

Abstract

With the rapidly growing demand for DNA analysis, the need for storing and processing large-scale genome data has presented significant challenges. This paper describes how the Genome Analysis Toolkit (GATK) can be deployed to an elastic cloud, and defines policy to drive elastic scaling of the application. We extensively analyse the GATK to expose opportunities for resource elasticity, demonstrate that it can be practically deployed at scale in a cloud environment, and demonstrate that applying elastic scaling improves the performance to cost tradeoff achieved in a simulated environment.
在弹性云中分析癌症基因组学
随着DNA分析需求的快速增长,存储和处理大规模基因组数据的需求提出了重大挑战。本文描述了如何将Genome Analysis Toolkit (GATK)部署到弹性云中,并定义了驱动应用程序弹性扩展的策略。我们对GATK进行了广泛的分析,以揭示资源弹性的机会,证明它可以在云环境中大规模部署,并证明应用弹性扩展可以提高性能,从而在模拟环境中实现成本权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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