Statistical Genetic Methods for Cancer Gene Studies

描述(申请人提供)：寻找基因决定因素 常见的复杂疾病是一项艰巨的任务，因为许多遗传和 环境因素，无论是单独的还是联合的，都会影响性格 表情。使用关联研究来应对这一挑战的方法是 变得越来越普遍，尤其是随着人类基因组的释放 序列。然而，有足够力量的大规模联想研究将 需要找到这些效应大小适中的基因。基于家庭的 协会的研究一直被证明不如 病例对照研究，但病例对照研究不能有效地利用数据 收集用于连锁研究和国家登记。因此，总体来说， 这个指导性提案的目标是开发和研究新的研究 关联性研究的设计和统计分析方法 前述两种设计的组合。具体来说，我们会： (1)检查我们提议的混合设计的抽样策略，以便 提供指南，使研究人员能够选择信息量最大的 研究对象。 (2)推导和评估将用于我们建议的混合方案的统计方法 设计。我们将考虑分层分析的方法，对于匹配的 设计，用于DNA池，并用于测试相互作用效果。 (三)发展和研究适合人口的统计方法 分层，因为我们建议的设计可能会受到影响 关于人口分层的问题。 (4)开发可用于设计和使用的人性化软件 对我们提议的混合动力设计进行分析。 此外，通过计划在以下方面进行的教学培训 统计遗传学和分子生物学，这项指导性的建议将 为我提供机会，为我奠定坚实的基础 从事涉及癌症基因研究的方法学研究。

DESCRIPTION (provided by applicant): Finding the genetic determinants of common complex disorders is a formidable task, since many genetic and environmental factors, either individually or in combination, influence trait expression. The use of association studies to tackle this challenge is becoming more widespread, especially with the release of the human genome sequence. However, large-scale association studies with sufficient power will be required to find these genes with modest effect sizes. Family-based association studies have consistently been shown to be less powerful than case-control studies, but case-control studies do not efficiently use the data collected for linkage studies and national registries. Therefore, the overall goal of this mentored proposal is to develop and investigate novel study designs and statistical analysis methods for association studies that are a combination of the two aforementioned designs. Specifically, we will: (1) examine sampling strategies for our proposed hybrid design in order to provide guidelines that enable researchers to choose the most informative subjects. (2) derive and evaluate statistical methods to be used for our proposed hybrid design. We will consider methods for stratified analyses, for matched designs, for DNA pooling, and for testing interaction effects. (3) develop and examine statistical methods that correct for population stratification, since our proposed designs may be susceptible to the effects of population stratification. (4) develop user-friendly software that can be used for the design and analysis of our proposed hybrid designs. Additionally, through the planned didactic training in areas including statistical genetics and molecular biology, this mentored proposal will provide me the opportunity to build a strong foundation upon which to build career conducting methodological research involving genetic studies of cancer.