Integration of phenotype data from multiple centers using ontologies

描述(申请人提供)：心血管疾病是美国和其他西方国家的主要死亡原因。虽然许多因素增加了心血管疾病的风险，但遗传和环境因素都被认为是危险因素。许多关键的生理学研究已经在多个品系的大鼠身上进行，以剖析心血管疾病的机制，包括高血压、心肌梗死和外周血管疾病。然而，这些数据集的价值受到限制，因为无法将表型结果与在不同品系或不同环境条件下进行的其他类似研究相结合。这项提议的目标是提供一种新颖而强大的方法来集成三个大型表型数据集，以允许科学界访问、可视化和分析数据，从而将生理特征附加到基因组中。为了实现这些表型数据集的集成，我们提出了：1.开发新的本体，并对现有的本体进行调整，以实现数据集成。利用三个主要的大鼠项目--高血压的分子遗传学、基因组应用的PhysGen计划和日本的国家大鼠生物资源项目--产生的心血管表型数据，将为大鼠表型数据常见的四个主要实验参数开发本体论：1)临床测量；2)分析类型；3)实验条件；4)大鼠品系样本。重点将放在与心血管表型相关的领域，其整体结构的创建允许扩展到其他表型领域和其他模式生物。2.开发数据和数据仓库集成的数据结构。将创建一个数据库，其中包含适当的表格和字段，用于存储与每项研究有关的数据以及与表型和实际表型值有关的四个实验参数。现有的三个数据集中的数据将被映射到适当的字段和本体，并加载到数据存储库中。3.提供对本体和集成数据集的公共访问。将在大鼠基因组数据库(RGD)上提供对综合数据集的访问，并为用户提供适当的数据挖掘、显示和下载工具。本体论将通过RGD ftp站点以OBO格式提供，并将提交给国家生物医学本体论中心，通过他们的生物门户网站获得。将开发包括在线视频和文本教程在内的教育工具。评价程序将包括从科学界获取和整合投入的方法。这些本体论、数据结构和存储库以及公共访问门户将把继续分析心血管疾病基因组基础所需的基本表型数据联系在一起。 公共卫生相关性：心血管疾病是美国和其他西方国家的主要死亡原因。将生理功能与基因组数据相结合，将使研究人员能够更快地识别与心血管疾病有关的基因。该项目的总体目标是为生理数据开发本体论和标准化数据格式，以实现大型生理数据集的集成，并将这些集成信息与现有的基因组资源联系起来，从而提高我们阐明疾病遗传基础的能力。

DESCRIPTION (provided by applicant): Cardiovascular disease is the leading cause of death in the United States and other Western countries. Although many factors add to the risk of cardiovascular disease, genetics and environmental factors have both been implicated as risk factors. Many key physiological studies have been performed on multiple rat strains to dissect the mechanisms of cardiovascular disease, including hypertension, myocardial infarction, and peripheral vascular disease. However, the value of these data sets is limited by the inability to integrate the phenotype results with other similar studies performed on different rat strains or under different environmental conditions. The goal of this proposal is to provide a novel and powerful approach to integrate three large phenotype data sets to allow the scientific community to access, visualize, and analyze data to attach physiological traits to the genome. To achieve the integration of these phenotype data sets, we propose: 1. Develop new and adapt existing ontologies for data integration. Using cardiovascular phenotype data generated from three major rat projects, SCOR-Molecular Genetics of Hypertension, the PhysGen Program for Genomic Applications, and the National BioResource Project for the Rat in Japan, ontologies will be developed for the four major experimental parameters common to rat phenotype data: 1) clinical measurement; 2) assay type; 3) experimental conditions; 4) sample rat strain. Emphasis will be on areas related to cardiovascular phenotypes with overall structures created to allow expansion to other phenotype areas and other model organisms. 2. Develop data structures for integration of data and data repository. A database will be created with appropriate tables and fields for storing data related to each study as well as the four experimental parameters related to phenotype and the actual phenotype values. Data in the three existing datasets will be mapped to the appropriate fields and ontologies and loaded into the data repository. 3. Provide public access to ontologies and integrated dataset. Access to the integrated dataset will be provided at the Rat Genome Database (RGD) with appropriate data mining, display and download tools for users. The ontologies will be made available in OBO format through the RGD FTP site and will be submitted to the National Center for Biomedical Ontologies for availability through their BioPortal. Educational tools including online video and text tutorials will be developed. Evaluation procedures will include approaches to obtain and integrate input from the scientific community. Together, these ontologies, data structure and repository, and the public access portal will tie together essential phenotype data needed to continue analysis of the genomic basis of cardiovascular diseases. PUBLIC HEALTH RELEVANCE: Cardiovascular disease is the leading cause of death in the United States and other Western countries. Combining physiological function with genomic data will allow researchers to more rapidly identify genes involved in cardiovascular disease. The overall goal of this project is to develop ontologies and standardized data formats for physiological data to enable integration of large physiological data sets and to link this integrated information with existing genomic resources, thus advancing our ability to elucidate the genetic basis of disease.