Virtual Machines and Cloud Computing for automated and portable sequence analysis

用于自动化和便携式序列分析的虚拟机和云计算

• 批准号: 7854153
• 负责人: W. Florian Fricke
• 金额: $ 67.48万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7854153
• 关键词: Address; Adopted; Arts; Bioinformatics; Biomedical Research; Blast Cell; Code; Communities; Complex; Computer software; Computers; Consultations; Consumption; DNA; Data; Data Set; Development; Discipline; Documentation; Drops; Ensure; Environment; Excision; Funding; Future; Generations; Genome; Genomics; Goals; Grant; Human; Human Microbiome; Human Resources; Individual; Institutes; Laboratory Research; Linux; Maps; Measures; Memory; Metagenomics; Metric; Microbe; Online Systems; Operating System; Outsourcing; Peer Review; Performance; Phylogeny; Process; Publications; RNA Sequences; RNA Splicing; Relative (related person); Reporting; Research; Research Infrastructure; Research Personnel; Resources; Review Literature; Ribosomal RNA; Running; Sampling; Science; Sequence Analysis; Services; Site; Software Tools; Source; Survey Methodology; Surveys; System; Technology; Testing; Time; Training; United States National Institutes of Health; Viral; Work; base; biocomputing; computer infrastructure; computing resources; cost; fungus; genome sequencing; human DNA; innovation; interoperability; meetings; metagenomic sequencing; microbiome; next generation; open source; outreach; parallel computing; parallel processing; programs; satisfaction; statistics; success; symposium; tool; virtual; web site

Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. Increasing amounts of sequence data are being generated in multiple biomedical research disciplines, particularly through the application of next-generation sequencing technologies to the genomic analysis of humans and their associated microbiome. However, the bioinformatic infrastructure necessary for sequence processing, requiring demanding software installations and access to powerful CPUs, currently presents a dramatic bottleneck for the further expansion of research in this field. Our proposal aims to address this problem through the generation of a portable, stand-alone Virtual Machine (VM) software package that combines all essential tools to perform basic Metagenomic, Viral and Eukaryotic sequence analysis. This VM will allow researchers to easily implement entire software pipelines locally or on server networks, independently of the operating system that is being used and without further installation steps. Furthermore, due to the mobility of the VM package, researchers will have the opportunity to outsource compute-intensive processing steps to external Cloud Computing networks that exist as free academic and commercial services. As part of the proposed project, we will assemble bioinformatics analysis pipelines for metagenomic, viral and eukaryotic genome sequencing projects with relevance to research on the human microbiome and the human host (Aim 1). Supported applications will include 16S rRNA-based phylogeny and community comparison, and identification, assembly, annotation and functional characterization of viral, bacterial and eukaryotic sequences from metagenomic HMP samples. In addition, pipelines for other increasingly relevant applications in this field will be provided for the removal of human DNA from HMP samples, eukaryotic and prokaryotic DNA and RNA sequence mapping, including SNP and splice site identification and de novo sequence assembly and annotation of eukaryotic microbes from the human microbiome, such as fungi and protists. Integrated analysis pipelines will be packaged into a VM, creating a stand-alone, push-button sequence analysis package (Aim 2), which will be optimized for performance on commercial and academic Clouds (Aim 3). Objective measures of the suitability of Clouds for next-generation sequence analysis will be determined and include runtime performance metrics, such as execution time and relative speedup, requirements on disk storage, memory, and data transfer throughput to and from Clouds. Outreach to the broad user community, including key collaborators utilizing Cloud platforms, will promote interoperability and development of standards for performing sequence analysis on Cloud platforms (Aim 4). Extensive documentation will be provided, including interactive online training seminars (webinars). User satisfaction, including software ease of use, quality of documentation, and value of instructional seminars will be surveyed. An advisory board will be established and used in reviewing all user statistics, performance metrics, technical developments and overall success of the project in conjunction with the Program Officer.

在此处输入文本，该文本是您的应用程序的新摘要信息。此部分的文本长度不得超过 30 行。 多个生物医学研究学科正在生成越来越多的序列数据，特别是通过将下一代测序技术应用于人类及其相关微生物组的基因组分析。然而，序列处理所需的生物信息基础设施需要高要求的软件安装和强大的CPU，目前为该领域研究的进一步扩展带来了巨大的瓶颈。我们的建议旨在通过生成便携式、独立的虚拟机（VM）软件包来解决这个问题，该软件包结合了所有必要的工具来执行基本的宏基因组、病毒和真核序列分析。该虚拟机将允许研究人员在本地或服务器网络上轻松实现整个软件管道，独立于正在使用的操作系统，并且无需进一步的安装步骤。此外，由于VM包的移动性，研究人员将有机会将计算密集型处理步骤外包给作为免费学术和商业服务存在的外部云计算网络。作为拟议项目的一部分，我们将为与人类微生物组和人类宿主研究相关的宏基因组、病毒和真核基因组测序项目组装生物信息学分析管道（目标 1）。支持的应用将包括基于 16S rRNA 的系统发育和群落比较，以及宏基因组 HMP 样本中病毒、细菌和真核序列的识别、组装、注释和功能表征。此外，还将为该领域其他日益相关的应用提供管道，用于从 HMP 样品中去除人类 DNA、真核和原核 DNA 和 RNA 序列作图，包括 SNP 和剪接位点识别以及从头序列组装和人类微生物组真核微生物（如真菌和原生生物）的注释。集成分析管道将打包到虚拟机中，创建独立的按钮式序列分析包（目标 2），并将针对商业和学术云上的性能进行优化（目标 3）。将确定云对下一代序列分析的适用性的客观衡量标准，包括运行时性能指标，例如执行时间和相对加速、对磁盘存储、内存的要求以及进出云的数据传输吞吐量。与广泛的用户社区（包括利用云平台的主要合作者）的联系将促进在云平台上执行序列分析的标准的互操作性和开发（目标 4）。将提供广泛的文档，包括交互式在线培训研讨会（网络研讨会）。将调查用户满意度，包括软件易用性、文档质量和教学研讨会的价值。将成立一个咨询委员会，并与项目官员一起审查所有用户统计数据、绩效指标、技术发展和项目的整体成功。