SOFTWARE FOR INTEGRATED LINKAGE AND ASSOCIATION ANALYSIS

用于集成链接和关联分析的软件

• 批准号: 6538906
• 负责人: Elizabeth R Hauser
• 金额: $ 27.28万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-07-01 至 2004-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6538906
• 关键词: chronic disease /disorder; computer program /software; computer simulation; computer system design /evaluation; family genetics; gene expression; genotype; human data; linkage mapping; mathematical model; method development

The genetic analysis of complex diseases holds enormous promise for increasing knowledge about the biologic mechanisms leading to common diseases such as heart disease, cancer, diabetes, and Alzheimer disease. However, the genetic analysis of complex disease is challenging because these diseases are likely due to a complex interplay of multiple genetic and environmental factors. As a result of this complexity, studies of common diseases require very large samples. New quantitative methods are needed which maximize the information obtained from each study by extending currently available methods and combining them with novel methods. Studies of complex disease require the use of multiple analytic approaches and an understanding of the advantage and disadvantage of each method as well as the ways in which the different analytic methods can complement each other to enhance understanding of genetic factors for a complex disease. The goal of this proposal is to develop new methods of linkage and association analysis, and to combine the new methods with existing linkage and association methods for nuclear families into single software package. Specifically we propose to: 1) extend existing affected-sib-pair linkage mapping software (Siblink) to allow consideration of phenotypic and environmental covariates, additional unlinked genes, and genotyping error; 2) provide enhancements to Siblink to allow for seamless estimation of empirical p-values and power, interval estimates of disease gene location, examination of robustness to model misspecification and incorporation of additional sibs; 3) develop methods for family-based association tests when parental genotyping information is missing; 4) develop methods to combine families with and without parents in a single analysis and for the use of multiple families from extended pedigrees; 5) perform simulation studies to examine optimal study design in the context of simultaneous linkage and association studies; 6) provide guidance as to the analysis method of choice under various conditions. The study of the genetics of a large number of common diseases currently underway at Duke University Center for Human Genetics and the University of Michigan provides a rich resource for application and assessment of these new methods to real data.

复杂疾病的遗传分析对增加有关导致常见疾病（例如心脏病，癌症，糖尿病和阿尔茨海默氏病）的生物学机制知识的知识具有巨大的希望。 但是，复杂疾病的遗传分析具有挑战性，因为这些疾病可能是由于多种遗传和环境因素的复杂相互作用所致。由于这种复杂性，对常见疾病的研究需要很大的样本。 需要新的定量方法，通过扩展当前可用的方法并将其与新方法结合起来，从而最大程度地提高了从每个研究获得的信息。 复杂疾病的研究需要使用多种分析方法，并了解每种方法的优势和缺点，以及不同的分析方法可以相互补充以增强对复杂疾病的遗传因素的理解。该提案的目的是开发新的链接和关联分析方法，并将新方法与现有的核心家庭链接和关联方法相结合，成为单个软件包。 具体而言，我们建议：1）扩展现有的受影响的SIB-PAIR链接映射软件（SIBLINK），以允许考虑表型和环境协变量，其他未连接基因以及基因分型误差； 2）为SIBLINK提供增强功能，以允许对经验P值和功率的无缝估计，疾病基因位置的间隔估计，检查鲁棒性的模型指定性指定和掺入其他SIBS； 3）当缺少父母基因分型信息时，开发基于家庭关联测试的方法； 4）开发在单个分析中与有和没有父母的家庭相结合的方法，并使用延长的家族中的多个家庭； 5）进行仿真研究，以同时联系和关联研究的背景下检查最佳研究设计； 6）提供有关在各种条件下首选分析方法的指导。 杜克大学人类遗传学中心和密歇根大学目前正在进行大量常见疾病的遗传学的研究为应用和评估这些新方法的真实数据提供了丰富的资源。