Design and Analysis of 2 Stage GWAS Study Using Next Generation Sequence Technolo

使用下一代测序技术的 2 阶段 GWAS 研究的设计和分析

• 批准号: 8006910
• 负责人: Paul Marjoram
• 金额: $ 22.52万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-28 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8006910
• 关键词: Address; Biology; Data Set; Disease; Future; Genetic; Genetic Variation; Genomics; Guidelines; Individual; Pattern; Performance; Phenotype; Sampling; Staging; Technology; Testing; Translating; Variant; design; genome wide association study; next generation

DESCRIPTION (provided by applicant): One of the most important challenges facing biology today is to understand how genetic variation between individuals translates into variation in phenotype, such as disease status. While the recent wave of genome-wide association studies has led to the discovery of a number of variants associated with disease, the vast majority of that variation remains unexplained. This project proposes to develop guidelines for the next step, the sequencing of samples in the associated regions to determine their complete patterns of genetic variation and thereby identify smaller sets of strongly associated variants that are associated with disease. This will be undertaken by comparing a variety of design and analysis approaches on a range of test datasets, thereby assessing the performance and utility of those approaches for future studies. RELEVANCE: The genomic era carries the promise of allowing us to uncover the genetic courses of disease. While some progress has been made to date, a large number of the genetic causes of disease are yet to be determined. The next wave of studies to address this issue will use next-generation sequencing technologies. The purpose of our proposal is to provide guidelines for the design and analysis of these studies. Such guidelines will leverage the newer of those studies.

描述（由申请人提供）：当今生物学面临的最重要挑战之一是了解个体之间的遗传变异如何转化为表型的变化，例如疾病状况。尽管最近的全基因组关联研究浪潮导致发现了许多与疾病相关的变异，但这种变异的绝大多数仍无法解释。该项目建议制定下一步的准则，即在相关区域中样本的测序，以确定其完整的遗传变异模式，从而确定与疾病相关的较小相关变体的较小集合。这将通过比较一系列测试数据集的各种设计和分析方法来进行，从而评估这些未来研究方法的性能和实用性。 相关性：基因组时代具有允许我们揭开疾病遗传学进程的希望。尽管迄今为止已经取得了一些进展，但尚未确定大量疾病的遗传原因。 解决此问题的下一波研究将使用下一代测序技术。我们建议的目的是为这些研究的设计和分析提供指南。这样的指南将利用这些研究的较新。