Theoretical Studies of Linkage Disequilibrium

该项目的长期目标是为以下方面开发统计和计算方法： 群体遗传学中的单倍型分析。随着人类基因组中大量遗传标记的可用性和基因分型技术的进步，在群体遗传学研究中对来自多个群体的大量个体中的数千个标记进行基因分型变得可行。对这些数据的分析提出了具有挑战性的统计和计算问题，需要进行理论和实证研究，以开发和评估统计方法，这些方法可以最好地提取最相关的信息，用于对感兴趣的参数进行统计推断。这些项目的具体目标是： (1)发展统计和计算方法，从多个群体中观察到的非定相标记数据推断单倍型频率;（2）发展标记选择的一般指南，以通过单倍型识别疾病易感性变体;（3）使用由单核苷酸多态性组成的单倍型以及来自多个群体的微卫星来推断群体参数以及局部重组率;（4）调查统计方法的力量，以确定已受到自然选择的染色体区域;（5）在将分发给科学界的计算机程序中实施和验证所开发的方法;以及（6）合作 与其他研究人员一起，将从本项目中获得的方法和知识应用于分析其他项目的数据。我们的方法将利用两个独特的功能，在收集的数据：大量的人口在世界各地和详尽的编目扩展染色体区域的单倍型。这些新的统计方法和用户友好的计算机程序的发展将提供有用的工具，人口遗传学研究和分析从其他项目收集的数据将导致更好地了解不同的人口之间的关系和不同的力量导致连锁不平衡模式在人类基因组。

The long-term objective of this project is to develop statistical and computational methods for the analysis of haplotypes in population genetics. With the availability of large numbers of genetic markers in the human genome and the advances in genotyping technology, it is becoming feasible in population genetic studies to genotype thousands of markers in a large number of individuals from multiple populations. The analysis of such data poses challenging statistical and computational issues and both theoretical and empirical studies are needed to develop and evaluate statistical methods that can best extract the most relevant information for statistical inference of parameters of interest. The specific aims of this projects are: (1) Develop statistical and computational methods to infer haplotype frequencies from the observed unphased marker data in multiple populations; (2) Develop general guidelines for marker selection to identify disease susceptibility variants through haplotypes; (3) Use haplotypes consisting of single nucleotide polymorphisms as well as microsatellites from multiple populations for inference on population parameters as well as local recombination rates; (4) Investigate the power of statistical methods to identify chromosomal regions that have been subject to natural selections; (5) Implement and validate the developed methodologies in computer programs that will be distributed to the scientific community; and (6) Collaborate with other investigators to apply the methods and knowledge gained from this project to analyze data from other projects. Our methods will exploit two unique features in the data to be collected: the large number of populations around the world and the exhaustive cataloguing of haplotypes in extended chromosomal regions. The developments of these novel statistical methods and user-friendly computer programs will provide useful tools on population genetic studies and the analysis of data collected from other projects will lead to better understanding of relationships among various populations and different forces leading to linkage disequilibrium patterns in the human genome.