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。虽然许多因素会增加心血管疾病的风险，但遗传和环境因素都被认为是风险因素。许多关键的生理学研究已经在多个大鼠品系上进行，以解剖心血管疾病的机制，包括高血压、心肌梗死和周围血管疾病。然而，由于无法将表型结果与其他在不同大鼠品系或不同环境条件下进行的类似研究相结合，这些数据集的价值受到限制。本提案的目标是提供一种新颖而强大的方法来整合三种大型表型数据集，使科学界能够访问，可视化和分析数据，以将生理性状附加到基因组上。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调整现有的本体。利用来自三大大鼠项目——高血压分子遗传学研究项目（score - molecular Genetics of Hypertension）、PhysGen基因组应用项目（PhysGen Program for Genomic Applications）和日本国立大鼠生物资源项目（National BioResource Project for the rat）——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)试验型；3)实验条件；样品鼠株。重点将放在与心血管表型相关的区域，创建整体结构以允许扩展到其他表型区域和其他模式生物。2. 为数据和数据存储库的集成开发数据结构。将创建一个数据库，其中包含适当的表和字段，用于存储与每个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。三个现有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。鼠基因组数据库（RGD）将提供对集成数据集的访问，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，并将通过其生物门户提交给国家生物医学本体论中心。将开发包括在线视频和文字教程在内的教育工具。评估程序将包括从科学界获取和整合投入的方法。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。

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.