Statistical and quantitative genetics

统计和数量遗传学

• 批准号: 8609114
• 负责人: Bruce S. Weir
• 金额: $ 4.91万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-05 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8609114
• 关键词: African American; Attention; Chromosomes; Complex; Data; Data Analyses; Development; Genes; Genetic Markers; Genome; Genome Scan; Hispanics; Individual; Link; Literature; Maps; Methodology; Methods; Population; Quantitative Genetics; Sampling; Statistical Methods; Structure; Testing; Variant; X Chromosome; density; genetic analysis; genetic association; human disease; public health relevance; trait

DESCRIPTION (provided by applicant): Thanks to technological advances in high-density genome scans, genetic association studies routinely have data for hundreds of thousand or millions of genetic markers across the entire genome. Despite these advancements, the mapping of many complex traits has proven to be difficult, illustrating the need for new and more powerful methods for the identification of loci that influence complex traits. Statistical methods for the analysis of genetic data have primarily been developed for markers on the autosomal chromosomes and significantly less attention has been given to the analysis of the X-chromosome, despite the potential for identifying X-linked genes that influence complex traits. This project is concerned with development and application of statistical methodology for the analysis of X-chromosome data. We will develop statistical methodology for association testing of X-linked variants in samples with related individuals as well as methodology for relatedness inference on the X. We will also develop statistical methodology for estimating and adjusting for population structure on the X-chromosome in samples from populations with admixed ancestry, such as African Americans and Hispanics.

描述（由申请人提供）：由于高密度基因组扫描的技术进步，遗传关联研究通常具有整个基因组中数十万或数百万遗传标记的数据。尽管取得了这些进展，但许多复杂性状的定位已被证明是困难的，这说明需要新的和更强大的方法来鉴定影响复杂性状的基因座。用于遗传数据分析的统计方法主要是针对常染色体上的标记而开发的，而对X染色体的分析的关注明显较少，尽管X染色体具有识别影响复杂性状的X连锁基因的潜力。该项目涉及X染色体数据分析的统计方法的开发和应用。我们将发展相关个体样本中X连锁变异的关联性检验的统计学方法，以及X连锁变异相关性推断的方法。我们还将开发统计方法，用于估计和调整来自混合血统人群（如非洲裔美国人和西班牙裔美国人）样本中X染色体上的人群结构。