Integration of phenotype data from multiple centers using ontologies

描述（由申请人提供）：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种大鼠品系上进行，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，这些数据集的价值是有限的，无法整合的表型结果与其他类似的研究在不同的大鼠品系或不同的环境条件下进行。该提案的目标是提供一种新颖而强大的方法来整合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，从而将生理性状与基因组联系起来。为了实现这些表型数据集的整合，我们提出：1。为数据集成开发新的和适应现有的本体。使用从三个主要大鼠项目（高血压的SCOR分子遗传学、基因组应用的PhysGen程序和日本大鼠的国家生物资源项目）生成的心血管表型数据，将为大鼠表型数据常见的四个主要实验参数开发本体：1）临床测量; 2）测定类型; 3）实验条件; 4）样品大鼠品系。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.为数据和数据存储库的集成开发数据结构。将使用适当的表格和字段创建数据库，用于存储与每项研究相关的数据以及与表型相关的四个实验参数和实际表型值。现有三个数据集中的数据将映射到适当的领域和本体，并载入数据储存库。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）中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。这些本体将通过RGD FTP站点以OBO格式提供，并将提交给国家生物医学本体中心，以便通过其BioPortal提供。将开发教育工具，包括在线视频和文字教程。评价程序将包括获取和综合科学界投入的方法。总之，这些本体、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和标准化数据格式，以整合大型生理数据集，并将此整合信息与现有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.