Function Annotation Core

摘要 该计划的最终目标是开发研究癌症的方法。一 它的一个重要方面是了解生物学，或功能，背后的大 将被分析的数据量。本计划中的四个项目将处理数据 和不同级别的注释。例如，将分析遗传变异数据， 在项目1中，基因和蛋白质数据用于项目2、3和4，而微生物组和 代谢物数据用于项目3。这些数据集的功能注释将 对于每个项目来说，正确分析数据和解释结果至关重要。关键 核心B的重点是通过提供注释数据的资源来支持这些项目。 核心将与核心D（数据分析和软件开发）密切合作， 其提供对集中式数据存储的支持。 该项目将利用现有的内部注释工具，例如ANNOVAR 用于遗传变异注释和PANTHER用于基因/蛋白质注释，并鉴定 外部资源，优先考虑并建立综合全面的基础设施 用于注释。该系统将允许我们注释和重新注释数据， 由核心D引入计划。保持所有注释都是最新的是至关重要的， 所以它应该经常从源头上进行更新。它还应该有一个用户友好的 接口，允许程序中的成员在 生成它们，浏览和识别感兴趣的数据并检索共享结果， 其他研究人员。

Abstract The ultimate goal of the Program is to develop methodologies to study cancer. One important aspect of it is to understand the biology, or function, underlying the large amount of data that will be analyzed. The four projects in this Program will deal with data and annotations at different levels. For example, genetic variation data will be analyzed in Project 1, gene and protein data is used in Project 2, 3 and 4, while microbiome and metabolites data is used in Project 3. Functional annotations to these datasets will be crucial for each project to properly analyze the data and interpret the results. The key focus of Core B is to support these projects by providing resources to annotate the data. The Core will work very closely with Core D (Data analysis and software development), which provides support in centralized data storage. The project will leverage the existing in-house annotation tools, for example, ANNOVAR for genetic variant annotation and PANTHER for gene/protein annotation, and identify external resources, prioritize and build an integrative and comprehensive infrastructure for annotation. The system will allow us to annotate and re-annotate data that are brought into the Program by Core D. It is crucial to maintain all annotations up to date, so it should make frequently updates from the source. It should also have a user-friendly interface to allow members in the Program to annotate the data while they are generating them, browse and identify the data of interest and retrieve shared results by other researchers.