Analysis and Annotation Pipeline for Functional Genomics

产品说明： 这项资助旨在为功能基因组学数据开发一个可扩展、可扩展的自动数据分析管道。功能基因组学，包括微阵列和蛋白质组学，正在迅速发展，数据集的规模迅速增加，新的分析方法每月出现。 由于没有事实上的标准来解决典型的实验问题，因此多个分析的应用是可取的，但由于所需的努力很少执行。此外，功能基因组学数据的分析通常是多步骤过程，在每个步骤中使用许多可能的方法（例如，用于图像分析、数据标准化、统计分析、数据挖掘），导致在使用多种分析时工作量的组合爆炸。 本申请中提出的功能基因组学数据管道将提供自动执行多种分析的能力，将提供用于添加新功能和数据类型的容易的可扩展性，将提供分布式计算环境以提供足够的计算能力，并且将集成自动注释以允许分析由生物学知识指导。该系统将利用企业Java Bean提供一个强大的服务器架构，Java服务器页面用于动态生成Web界面，以及面向对象的设计模式，以优化软件架构。通过使用结合Java反射机制的策略设计模式，该系统将在操作期间可扩展。功能基因组学数据集将被封装在数据对象中，包括NCI caBIO对象的链接，以利用NCI生物信息学中心的数据资源。此外，还可以从网站和通过分布式注释系统检索注释。文档和测试将与开发同时进行，并将在设计和部署期间集成最终用户以调整用户界面。 最终的系统将大大提高研究人员充分探索不断增长的数据集的能力，并根据更大的生物知识库解释他们的实验结果。它将完全支持并向社区开源发布。

DESCRIPTION: This grant proposes the development of an extendable, scalable automated data analysis pipeline for functional genomics data. Functional genomics, including microarrays and proteomics, is evolving quickly, with data sets increasing rapidly in size and new analysis methodologies appearing monthly. Because there are no de facto standards for addressing typical experimental questions, the application of multiple analyses is desirable, but rarely performed due to the effort required. Furthermore, the analysis of functional genomics data is generally a multi-step process, with many possible methods in use at each step (e.g., for image analysis, data normalization, statistical analysis, data mining), leading to a combinatorial explosion of effort when using multiple analyses. The functional genomics data pipeline proposed in this application will provide the ability to automatically perform multiple analyses, will provide easy extendibility for adding new functions and data types, will provide a distributed computing environment to provide adequate computational power, and will integrate automated annotation to allow analyses to be guided by biological knowledge. The system will utilize Enterprise Java Beans to provide a robust server architecture, Java server pages for dynamic generation of web interfaces, and object oriented design patterns to optimize the software architecture. The system will be extendable during operation through use of the Strategy design pattern coupled to the Java reflection mechanism. Functional genomics data sets will be encapsulated within data objects that include links to the NCI caBIO objects to utilize the NCI Center for Bioinformatics data resources. In addition, annotations will be retrievable from web sites and through the Distributed Annotation System. Documentation and testing will proceed in parallel with development, and will integrate end users during design and deployment to tune the user interface. The final system will provide dramatic improvements in researchers' abilities to fully explore their growing data sets and to interpret their experimental results in light of the larger biological knowledge bases. It will be fully supported and released to the community open source.