Robust Methods for Complex Trait Association Mapping

复杂性状关联映射的稳健方法

• 批准号: 7031501
• 负责人: Fei Zou
• 金额: $ 20.44万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2010-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7031501
• 关键词: computer program /software; computer system design /evaluation; functional /structural genomics; genetic markers; genetic polymorphism; genetic susceptibility; genotype; haploidy; human data; linkage disequilibriums; linkage mapping; method development; population genetics; statistics /biometry

DESCRIPTION (provided by applicant): The objectives of this research are to address some statistical issues related to association mapping (or disequilibrium mapping) for complex traits. We plan to develop robust, yet efficient statistical methods to deal with some important problems that have not been addressed or have not been fully resolved in the literature. The specific aims are: 1. To develop simple and robust techniques for assessing population stratification when anonymous markers are available, but are not necessarily in linkage equilibrium with each other. 2. To develop an efficient method for capturing the simultaneous effects of multiple genetic variants that individually make only a small contribution to the total disease risk, while controlling the overall false positive rate. 3. To explore robust non-parametric methods for estimating and assessing haplotypes associated with disease: mapping disease-associated haplotypes without pre-assigning window size of the haplotype; mapping multiple pre-disposing haplotypes; and mapping when haplotypes cannot be discerned unambiguously. Software to carry out the specific aims will be developed and implemented in the R or C computing environment for public distribution.

描述（由申请人提供）：本研究的目的是解决与复杂性状有关的关联映射（或不平衡映射）有关的一些统计问题。我们计划开发强大而有效的统计方法，以处理一些尚未解决或尚未完全解决的重要问题。具体目的是： 1。开发简单而强大的技术来评估匿名标记时人口分层，但不一定彼此之间处于链接平衡。 2。开发一种有效的方法来捕获多种遗传变异的同时效应，该方法单独地对总疾病风险做出很小的贡献，同时控制整体假阳性率。 3。探索可靠的非参数方法来估计和评估与疾病相关的单倍型：映射与疾病相关的单倍型，而没有预分配单倍型的窗户大小；绘制多个预插入单倍型；当单倍型不能明确辨别时地图。 将在R或C计算环境中开发和实施以进行公共分发的软件。