SI2-SSE: Reducing the Complexity of Comparative Genomics with Online Analytical Processing

SI2-SSE：通过在线分析处理降低比较基因组学的复杂性

• 批准号: 1047896
• 负责人: Cynthia Gibas
• 金额: $ 44.83万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1047896&HistoricalAwards=false
• 关键词: SI2; SSE; Reducing; Complexity; Comparative

Genome comparison is a common bioinformatics analysis task, but a survey of the literature suggests that comparative genomic studies are done in an ad hoc, investigator-dependent, and non-reproducible fashion. Comparative genomics analysis questions can generally be formulated as set queries: what differentiates genome A from genome B, or from a broader group of its taxonomic neighbors? This project will develop a data warehouse-type database system optimized for comparative genomics that is particularly suited to answer these kinds of questions. It will store sequence-linked biological data in a way that supports OLAP (On-Line Analytical Processing) and complex set-based queries. A workflow tool will be developed for guiding the user through core comparative genomic operations, and will serve as an interface for populating the data warehouse. An interactive query tool will allow the user to easily construct complex questions about the data. Set-based as well as individual record results will be presented to the user in a way that can be easily browsed, compared, and exported.The system will enable the user to generate and compare genomic feature sets following a guided workflow defined by and incorporating common elements of analysis used in current microbial genome studies. Parameters and results from each step in the process will be tracked for later reporting. The system will enable both biology-driven comparison of genomic feature sets, and perhaps more importantly systematic inquiry into and comparison of bioinformatics analysis results obtained at each workflow stage. All software and database structures developed in this project will be made available under an open-source license and as runnable virtual machine images. The latter will make it possible for scientists to get started without complicated installation and configuration procedures, and instead focus on their research questions. All user-facing parts of the software will be accessible through a web browser, making use of the latest developments in browser-based interaction and HTML5. A diverse group of graduate students will receive inter-disciplinary training in this project, and K-12 and underrepresented groups will be included in through ongoing partnerships with the STARS Alliance program.

基因组比较是一项常见的生物信息学分析任务，但文献调查表明，比较基因组研究是在一个特设的，依赖于分析仪，和不可重现的方式。比较基因组学分析问题通常可以表述为集合查询：基因组A与基因组B或与其更广泛的分类学邻居有什么区别？本项目将开发一个针对比较基因组学优化的数据仓库型数据库系统，特别适合回答这类问题。它将以支持OLAP（在线分析处理）和复杂的基于集合的查询的方式存储与序列相关的生物数据。将开发一个工作流程工具，用于指导用户完成核心比较基因组操作，并将作为填充数据仓库的界面。交互式查询工具将允许用户轻松地构建有关数据的复杂问题。系统将以易于浏览、比较和导出的方式向用户呈现基于集合的以及单个记录的结果。该系统将使用户能够按照由当前微生物基因组研究中使用的分析的共同元素定义的指导工作流程生成和比较基因组特征集合。将跟踪流程中每个步骤的参数和结果，以便以后报告。该系统将使生物学驱动的基因组特征集的比较，也许更重要的是系统的查询和比较在每个工作流程阶段获得的生物信息学分析结果。该项目中开发的所有软件和数据库结构都将在开源许可证下提供，并作为可运行的虚拟机映像。后者将使科学家能够在没有复杂的安装和配置程序的情况下开始工作，而是专注于他们的研究问题。该软件所有面向用户的部分都将通过网络浏览器访问，利用基于浏览器的交互和HTML5的最新发展。一个多样化的研究生群体将在这个项目中接受跨学科培训，K-12和代表性不足的群体将通过与STARS联盟计划的持续合作关系被纳入其中。