Development of statistical genetics methodology

统计遗传学方法的发展

• 批准号: 6830376
• 负责人: Joan Ellen Bailey-Wilson
• 金额: --
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6830376
• 关键词: biotechnology; brca gene; clinical research; computer simulation; cooperative study; evaluation /testing; family genetics; forensic medicine; gene mutation; genetic carriers; genetic markers; genetic registry /resource /referral center; genetic screening; human data; linkage mapping; method development; siblings; statistics /biometry

A major project of this section is the development of new statistical genetics methodology as prompted by the needs of our applied studies. This year Dr. Bailey-Wilson worked on development of several new methods. We have continued our collaboration with Dr. Silvano Presciuttini from the University of Pisa, on the development of simplified, approximate and stepwise procedures for using genetic markers to differentiate siblings and other types of relative pairs from unrelated individuals. This methodology has applications in linkage analysis and in forensics. Additional development has been done on these methods this year and a paper was published. This collaboration has also initiated a new project, development of better methods for predicting mutation carrier status for BRCA1 in Italian families. A paper has been submitted presenting this work. The third project, in collaboration with Dr. Jim Malley at CIT, NIH, is the development of a new method for family based association tests that appears considerably more powerful than the TDT but more robust to false positives than is case-control association. Extensive simulation studies have been performed to test the performance of this method. A paper demonstrating the properties of this method on simulated data was recently published in Genetic Epidemiology and another paper Biometric Journal was published in this fiscal year. The fourth project, also in collaboration with Dr. Malley and with Dr. Dan Naiman of Johns Hopkins University, is an application of less conservative methods of correcting for multiple testing in human genetics analysis. This method has been applied to Genetic Analysis Workshop 13 data this year, and a paper is in press. A manuscript was also published this year detailing the theoretical basis of this work. Finally, work is being done in this section to improve upon the computer implementation of various existing analysis methods. These projects are ongoing.

由于应用研究的需要，本节的一个主要项目是发展新的统计遗传学方法。今年，贝利-威尔逊博士致力于开发几种新方法。我们继续与比萨大学的Silvano Presciuttini博士合作，开发简化、近似和逐步的程序，利用遗传标记来区分兄弟姐妹和其他类型的亲属对与不相关的个体。这种方法在关联分析和法医学中都有应用。今年对这些方法进行了进一步的开发，并发表了一篇论文。这项合作还启动了一个新的项目，开发更好的方法来预测意大利家庭中BRCA1突变携带者的状态。已经提交了一篇介绍这项工作的论文。第三个项目是与美国国立卫生研究院CIT的Jim Malley博士合作，开发一种基于家庭的关联检测的新方法，这种方法似乎比TDT更有效，但比病例对照关联更容易出现假阳性。已经进行了大量的仿真研究来测试该方法的性能。最近在《遗传流行病学》上发表了一篇论文，展示了该方法在模拟数据上的特性，另一篇论文在本财政年度发表在《生物计量学杂志》上。第四个项目也是马利博士和约翰霍普金斯大学（Johns Hopkins University）的丹·内曼（Dan Naiman）博士合作的，是在人类基因分析中应用不那么保守的方法来校正多重测试。该方法已应用于今年遗传分析研讨会13的数据，并有一篇论文正在出版中。今年还发表了一份手稿，详细介绍了这项工作的理论基础。最后，本节所做的工作是改进各种现有分析方法的计算机实现。这些项目正在进行中。