Development of statistical genetics methodology

这一部分的一个主要项目是开发新的统计遗传学方法，以满足我们应用研究的需要。今年，贝利-威尔逊博士致力于几种新方法的开发。我们继续与比萨大学的Silvano Presciuttini博士合作，开发简化、近似和循序渐进的程序，使用遗传标记区分兄弟姐妹和其他类型的亲属对与不相关的个人。这种方法在连锁分析和法医学中有应用。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项目，开发更好的方法来预测意大利家庭中BRCA1的突变携带者状态。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测试的新方法，该方法似乎比TDT更强大，但比病例对照关联更能抵抗假阳性。为了测试该方法的性能，已经进行了大量的仿真研究。最近在《遗传流行病学》上发表了一篇在模拟数据上展示这种方法的特性的论文，另一篇论文《生物统计学杂志》也在本财年发表。第四个项目也是与马利博士和约翰斯·霍普金斯大学的丹·奈曼博士合作的，是在人类遗传学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13号遗传分析车间的数据，一篇论文正在出版中。今年还出版了一份手稿，详细阐述了这项工作的理论基础。最后，本节正在开展工作，以改进各种现有分析方法的计算机实施。这些项目正在进行中。

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.