Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline
Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline
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DOI：
10.1074/mcp.o114.043380
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发表时间：
2015-02-01
影响因子：
7
通讯作者：
Moritz, Robert L.
中科院分区：
文献类型：
--
作者：
Slagel, Joseph;Mendoza, Luis;Moritz, Robert L.
云计算以服务的形式提供可扩展的按需计算周期和存储，通过为所有实验室提供简单、可扩展且负担得起的大规模计算，而不受地理位置或信息技术专业知识的影响，云计算有可能加速基于质谱学的蛋白质组学研究。我们为跨蛋白质组管道提供了新的云计算功能，这是一套免费和开源的工具，用于处理和分析串联质谱仪数据集。在亚马逊网络服务云计算的支持下，跨蛋白质管道现在可以为所有用户访问大规模计算资源，仅受可用的亚马逊网络服务基础设施的限制。跨蛋白质管道在完全托管在亚马逊网络服务上的环境中运行，所有软件和数据都驻留在云资源上，以处理大型搜索研究。此外，它还可以在本地计算机上运行，并在Amazon Elastic Compute Cloud服务上启动计算密集型任务，以极大地减少分析时间。我们描述了新的跨蛋白质管道云服务组件，比较了各种弹性计算云服务实例类型的相对性能和成本，并提供了在线教程，使用户能够了解如何使用跨蛋白质管道快速部署云计算技术。我们提供了在给定工作规模的情况下估计必要的计算资源和成本的工具，并通过在9小时内通过四个蛋白质组搜索引擎以非常低的成本执行超过1100个串联质谱仪文件，展示了云支持的跨蛋白质组管道的使用。
Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost.