Human QTL Mapping With Selected Samples

选定样本的人类 QTL 作图

• 批准号: 7076134
• 负责人: Eleanor Feingold
• 金额: $ 21.24万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7076134
• 关键词: analytical method; computer program /software; computer simulation; computer system design /evaluation; family genetics; gene expression; genetic models; human population genetics; linkage mapping; method development; phenotype; quantitative trait loci; siblings; statistics /biometry

DESCRIPTION (provided by applicant): One of the most important directions in current biomedical research is the quest to understand the genetic contributions to complex diseases. A critical part of many such investigations is the use of linkage analysis to find possible disease susceptibility loci. Recently, there has been substantial interest in using linkage methods designed for quantitative phenotypes as a tool for finding genes associated with diseases. For example, this approach has been applied to schizophrenia, type II diabetes, hypertension, and heart disease. This growth in interest in QTL mapping in humans has been accompanied by a great deal of new work on statistical methods, but little of that work has dealt with selected samples, which are arguably more common than population samples for human studies. The general aim of this grant is to develop powerful statistics for QTL mapping with selected samples and powerful designs for selecting such samples. The specific aims are as follows. 1) Develop and compare statistics for selectively sampled nuclear families. 2) Develop and compare statistics for selectively sampled extended pedigrees. 3) Develop end-user software to implement all of the best methods and make them readily available to investigators doing mapping studies. 4) Investigate the relative power of different sampling schemes under various genetic models.

描述（由申请人提供）：当前生物医学研究中最重要的方向之一是寻求了解复杂疾病的遗传贡献。许多此类调查的关键部分是使用连锁分析来寻找可能的疾病易感性位点。最近，人们对使用设计用于定量表型的连锁方法作为发现与疾病相关的基因的工具产生了很大的兴趣。例如，这种方法已被应用于精神分裂症，II型糖尿病，高血压和心脏病。对人类QTL作图的兴趣的增长伴随着大量关于统计方法的新工作，但这些工作很少涉及选定的样本，这些样本可以说比人类研究的群体样本更常见。该基金的总体目标是开发用于QTL定位的强有力的统计数据和用于选择这些样本的强有力的设计。具体目标如下。1)编制和比较有选择地抽样的核心家庭的统计数字。2)发展和比较选择性抽样的扩展谱系的统计数据。3)开发最终用户软件以实施所有最佳方法，并使其随时可供进行绘图研究的研究人员使用。4)研究不同遗传模型下不同抽样方案的相对功效。