Statistical Methods to Map Genes for Complex Traits

绘制复杂性状基因图谱的统计方法

• 批准号: 6789446
• 负责人: HONGYU ZHAO
• 金额: $ 23.29万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-02-01 至 2005-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6789446
• 关键词: Internet; biomedical resource; biotechnology; computer program /software; computer simulation; computer system design /evaluation; family genetics; gene environment interaction; gene expression; gene interaction; genetic markers; genetic models; genetic susceptibility; genotype; human data; human population genetics; linkage mapping; mathematical model; model design /development; quantitative trait loci; statistics /biometry

DESCRIPTION (provided by applicant): The long-term objective of this project is to develop novel and powerful statistical methods to identify genes underlying complex traits. With the availability of large numbers of genetic markers in the human genome, it is becoming feasible in genetic association studies to genotype thousands of markers and to saturate candidate regions with many tightly linked markers. The analysis of such data poses challenging statistical issues and both theoretical and empirical studies are needed to develop and evaluate statistical methods that can best extract the most relevant information. The specific aims of this projects are: (1) Develop statistical methods to appropriately control for population stratification in an association study, both for qualitative traits and for quantitative traits; (2) Develop statistical methods to study associations between multiple tightly linked markers and complex traits of interest, both for samples consisting of unrelated individuals and for samples consisting of pedigrees; (3) Compare statistical efficiencies and the overall cost for various genotyping strategies in association studies; and (4) Develop computer programs that implement the statistical methods developed in this project and distribute them to the scientific community. We will also apply these methods to map complex disease genes through our extensive collaborations. The developments of these novel statistical methods and user-friendly computer programs will provide biomedical researchers with important tools to identify genes underlying complex traits .

描述（由申请人提供）：该项目的长期目标是开发新的和强大的统计方法，以确定复杂性状的基因。随着人类基因组中大量遗传标记的可用性，在遗传关联研究中对数千个标记进行基因分型并使候选区域与许多紧密连锁的标记饱和变得可行。此类数据的分析提出了具有挑战性的统计问题，需要进行理论和实证研究来开发和评估能够最好地提取最相关信息的统计方法。该项目的具体目标是：（1）开发统计方法，以适当控制关联研究中的群体分层，包括质量性状和数量性状;（2）开发统计方法，以研究多个紧密连锁的标记与感兴趣的复杂性状之间的关联，包括由无关个体组成的样本和由谱系组成的样本;（3）比较关联研究中各种基因分型策略的统计效率和总成本;（4）开发计算机程序，实现本项目中开发的统计方法，并将其分发给科学界。我们还将通过广泛的合作将这些方法应用于绘制复杂的疾病基因。这些新的统计方法和用户友好的计算机程序的发展将为生物医学研究人员提供重要的工具，以确定复杂性状的基因。