Genome-wide Association in Families: Data Integrity, Design and Methods Issue

家庭全基因组关联：数据完整性、设计和方法问题

• 批准号: 7246523
• 负责人: JEFFREY R O'CONNELL
• 金额: $ 28.98万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-15 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7246523
• 关键词: Accounting; Address; Adult; Age related macular degeneration; Algorithms; Amish; Complex; Coronary heart disease; Data; Depth; Detection; Development; Disease; Disease susceptibility; Enrollment; Family; Gene Frequency; Genes; Genetic; Genome; Genotype; Goals; Haplotypes; Heart; Heart Diseases; Heritability; Individual; Intervention; Linkage Disequilibrium; Methods; Mutation; Myocardial Infarction; Numbers; Phenotype; Population; Process; Property; Rate; Recombinants; Reporting; Research Design; Research Personnel; Risk; Risk Factors; Sample Size; Sampling; Single Nucleotide Polymorphism; Speed; Surveys; Testing; Variant; base; cost; data integrity; density; design; falls; family structure; genetic pedigree; genome wide association study; heart disease risk; improved; microbial alkaline proteinase inhibitor; novel; programs; success; trait; transmission process

DESCRIPTION (provided by applicant): Extensive genome-wide single nucleotide polymorphisms (SNPs) are now available. Theoretically, we can systematically consider all the regions of the genome to identify those regions associated with disease susceptibility or unfavorable risk factors. Important issues need to be resolved however, before we can practically use all the genetic information in genome-wide association studies. Methods need to be developed to detect and resolve genotyping errors and we need new, analytical strategies designed specifically for family data that will account for multiple comparisons. Many large family-based studies, including our own, were initiated with the goal of first detecting linkage to identify chromosomal regions likely to harbor mutations having relatively large effects on important risk factors for heart disease. One of our studies, the Heritability and Phenotype Intervention (HAPI) Heart Study, includes extensive coronary heart disease risk factor data and 500,000 SNPs on 900 adults in Old Order Amish pedigrees. Our families are very suitable for genome-wide association studies and they offer special opportunities, compared to population-based samples, because families provide a direct test of allelic transmissions. This application addresses two specific issues pertaining to genome-wide association studies in families. One relates to development, implementation, testing, and dissemination of efficient ways to clean and process genome-wide SNP data and then create haplotypes. The other relates to developing analytic strategies that combine information from population- and transmission-based association tests to improve power, minimize false positive rates, and enhance efficiency for detecting SNP-trait associations.

描述（由申请人提供）：现在可以使用广泛的全基因组单核苷酸多态性（SNP）。从理论上讲，我们可以系统地考虑基因组的所有区域，以识别与疾病易感性或不利危险因素相关的区域。但是，在我们可以实际使用全基因组关联研究中的所有遗传信息之前，需要解决重要的问题。需要开发方法来检测和解决基因分型错误，我们需要专门为家庭数据设计的新的分析策略，这些策略将考虑多个比较。 许多大型基于家庭的研究，包括我们自己的研究，其目的是首先检测连接，以识别可能携带可能对心脏病重要危险因素影响相对较大影响的突变的染色体区域。我们的研究之一是，遗传力和表型干预（HAPI）心脏研究包括广泛的冠状动脉疾病危险因素数据和500,000个SNP，对900名成年人的旧秩序Amish谱系。我们的家庭非常适合全基因组的关联研究，与基于人群的样本相比，它们提供了特殊的机会，因为家庭提供了对等位基因传播的直接测试。 该申请解决了与家庭全基因组关联研究有关的两个特定问题。 一个涉及开发，实施，测试和传播有效的方法来清洁和处理全基因组SNP数据，然后创建单倍型。 另一个涉及开发分析策略，这些分析策略结合了基于人群和传输的关联测试的信息，以提高功率，最大程度地降低假阳性率，并提高检测SNP特征关联的效率。