Statistical Analysis of Genetic Analysis Workshop 12 Dat

遗传分析研讨会12数据的统计分析

基本信息

批准号：
6555962
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
项目类别：
财政年份：
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/6555962
关键词：
clinical research computer data analysis computer simulation cooperative study data collection methodology /evaluation family genetics genetic recombination genome human data linkage disequilibriums method development quantitative trait loci statistics /biometry workshop

项目摘要

This project involved analysis of a simulated dataset from the Genetic Analysis Workshop 12. A set of data for a complex qualitative trait was simulated by the data organizing committee of the GAW12. We used these data to compare the power of two new family-based tests of linkage disequilibrium that are being developed by me and my collaborators to several other implementations of the published Transmission Disequilibrium Test (TDT). We showed that none of these tests had adequate power in the small samples originally supplied, but that when all the replicates were combined to yield a large dataset, then all the methods had good power to detect loci with very small effects on the trait at genome-wide significance levels. One of our new methods was particularly successful in that we were able to show that it yields good estimates of both the recombination fraction and a generalized measure of association, something that the TDT does not accomplish. Preparation of a paper presenting these results was completed in this fiscal year and it was recently published in Genetic Epidemiology. In addition, Dr. Bailey-Wilson was invited to write another paper summarizing the results of a section of the GAW12 Workshop presentations dealing with association studies. This paper has also been recently published in Genetic Epidemiology. This project is now completed.

该项目涉及对基因分析研讨会12的模拟数据集的分析。GAW12的数据组织委员会模拟了复杂定性性状的一组数据。我们使用这些数据比较了我和我的合作者正在开发的两个基于家庭的链接不平衡测试的功能，这些测试与已发布的传输不平衡测试（TDT）的其他几个实现。我们表明，这些测试都没有足够的功率在最初提供的小样本中具有足够的功率，但是当将所有重复键合并以产生大型数据集时，所有方法都具有良好的能力来检测基因座，对基因组显着性水平的性状影响很小的影响很小。我们的新方法之一尤其成功，因为我们能够证明它可以对重组分数和广义衡量关联量产生良好的估计，这是TDT无法完成的。提出这些结果的论文的准备工作在本财政年度完成，最近发表在遗传流行病学上。此外，邀请贝利·威尔森（Bailey-Wilson）博士撰写另一篇论文，总结了有关关联研究的GAW12研讨会演示的一部分的结果。本文最近也发表在遗传流行病学上。该项目现已完成。