Analysis of rare variants & population structure

罕见变异分析

• 批准号: 8262854
• 负责人: Sharon Browning
• 金额: $ 23.69万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8262854
• 关键词: Accounting; Address; African American; Area; Computer software; Data; Data Analyses; Data Set; Disease; Distant; Ethnic Origin; Etiology; European; Genes; Genetic; Heritability; Individual; Instruction; Lead; Measures; Methodology; Methods; Population; Population Genetics; Quantitative Genetics; Sampling; Sequence Analysis; Statistical Methods; Structure; Testing; Ursidae Family; Variant; Weight; Work; cohort; design; genetic association; genome wide association study; improved; infancy; insight; interest; simulation; statistics; trait

PROJECT SUMMARY (See instructions): Genetic association analysis of rare variants is an area of growing importance in genetics. Rare variants may explain a large portion of the tieritability that has not been explained by common variants, and will lead to new insights into the aetiology of common diseases. Increasing amounts of sequence data are being generated in order to investigate rare variants; however, statistical methods for analysis of these data are in their infancy. We will develop statistical methodology to leverage genome-wide association data for rare variant analysis through imputation, haplotypic testing and selection of samples for sequencing, and we will compare methods for rare variant association analysis. We will also develop statistical methodology to detect population structure and correct for it in association analysis, with a particular focus on rare variant analysis.

项目摘要（参见说明）： 罕见变异的遗传关联分析是遗传学中日益重要的领域。罕见变异可能解释了常见变异无法解释的大部分可靠性，并将带来对常见疾病病因学的新见解。为了研究罕见变异，正在生成越来越多的序列数据；然而，分析这些数据的统计方法还处于起步阶段。我们将开发统计方法，通过插补、单倍型测试和选择测序样本，利用全基因组关联数据进行罕见变异分析，并且我们将比较罕见变异关联分析的方法。我们还将开发统计方法来检测 群体结构并在关联分析中对其进行纠正，特别关注罕见变异分析。