A Genetic Association Research Statistical Framework

遗传关联研究统计框架

• 批准号: 7225273
• 负责人: ROSS LAZARUS
• 金额: $ 49.95万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-01 至 2009-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7225273
• 关键词: Address; Adoption; Algorithms; Alleles; Asthma; Bioconductor; Bioinformatics; Cardiovascular Diseases; Clinical; Code; Collaborations; Communities; Complex; Computer software; Count; Data; Databases; Development; Diabetes Mellitus; Disease; Disease Association; Documentation; Education; Educational workshop; Engineering; Ensure; Environment; Environmental Exposure; Experimental Designs; Family; Frequencies; Funding; Genes; Genetic; Genetic Research; Genetic Variation; Genomics; Genotype; Goals; Hand; Harvest; Imagery; Laboratories; Language; Leadership; Learning; Linkage Disequilibrium; Metadata; Methods; Motivation; Output; Pharmaceutical Preparations; Pharmacogenetics; Phenotype; Phylogenetic Analysis; Population Genetics; Production; Productivity; Public Health; Publications; Range; Research; Research Infrastructure; Research Personnel; Research Project Grants; Resources; Role; Sample Size; Services; Solid; Source; Source Code; Standards of Weights and Measures; Statistical Methods; Testing; Training; United States National Institutes of Health; Variant; Visual; Work; base; case control; data structure; design; disease characteristic; experience; field study; file format; gene environment interaction; gene interaction; genetic analysis; genetic association; genetic epidemiology; innovation; insight; novel; open source; programs; research study; skills; tool; trait

DESCRIPTION (provided by applicant): Insight into genetic contributions to common, complex diseases of increasing public health importance such as asthma, diabetes and cardiovascular disease, is growing relatively slowly. Practical access barriers to newer bioinformatic resources and to appropriate statistical methods impede progress. Leveraging the existing R language and Bioconductor framework, an integrated suite of applications supporting activities common to complex disease association research will be created, directly addressing those barriers. Specific aims include software support for importing experimental data and genomic annotation; methods for statistical power calculations and for selecting maximally informative subsets of markers during experimental design; methods for visualizing and summarizing experimental results; established and recently developed methods supporting statistical inference on single markers, multiple markers and on the epistatic and gene by environment interactions characteristic of these diseases and needed for emerging fields of study such as pharmacogenetics. These deliverables will share a coherent user interface and common data structures, and will be accompanied by tutorials, example code and data, introductory and advanced documentation for users, and detailed source code and technical documentation for methods developers. The resulting packages will be widely distributed through the existing Bioconductor network and through the I(2)B(2) NCBC, as an immediately usable, open-source, interoperable and flexible genetic association experimental design and analysis software suite. Method developers will gain access to an integrated framework and a user base for building and distributing their work. Researchers will gain free and ready access to an increasingly rich range of bioinformatic resources and new statistical methods for genetic association analysis, because many existing practical challenges in their installation and use will have been overcome. Developed in the context of airways disease, the software will be immediately and directly applicable to genetic research in other common, complex disorders.

描述（由申请人提供）：对哮喘、糖尿病和心血管疾病等公共卫生重要性日益增加的常见复杂疾病的遗传贡献的了解增长相对缓慢。获取新的生物信息资源和适当的统计方法的实际障碍阻碍了进展。利用现有的R语言和Bioconductor框架，将创建一套集成的应用程序，支持复杂疾病关联研究中常见的活动，直接解决这些障碍。具体目标包括：为导入实验数据和基因组注释提供软件支持;统计功效计算方法和在实验设计过程中选择最大信息量的标记物子集的方法;可视化和总结实验结果的方法;已建立和最近开发的支持对单个标记进行统计推断的方法，多个标记和上位性和基因与环境的相互作用，这些疾病的特点，并需要新兴的研究领域，如药物遗传学。这些交付品将共享一致的用户界面和通用数据结构，并将附带教程、示例代码和数据、用户入门和高级文档，以及方法开发人员的详细源代码和技术文档。由此产生的软件包将通过现有的Bioconductor网络和I（2）B（2）NCBC广泛分发，作为一个立即可用的，开源的，可互操作的和灵活的遗传关联实验设计和分析软件套件。方法开发人员将获得一个集成的框架和一个用户基础，用于构建和分发他们的工作。研究人员将获得免费和随时访问越来越丰富的生物信息学资源和新的统计方法进行遗传关联分析，因为许多现有的实际挑战，在其安装和使用将被克服。该软件是在气道疾病的背景下开发的，将立即直接适用于其他常见复杂疾病的遗传研究。