Quantitative Methods for Linkage and Associated Studies

该项目的目标是开发改进的定量方法，用于分析复杂疾病的家庭和人口研究中收集的遗传数据，并将这些方法应用于易于使用的计算机程序中。需要这种方法来解开常见疾病的复杂遗传基础。 新的方法将被开发用于以下任务：在任意大和复杂的谱系中对定性和定量性状进行更快和更节省内存的多点分析;检测单倍型与疾病的关联;多点连锁不平衡分析;基于SNP的关联研究。新技术允许收集越来越多的来自家庭和人群的常见疾病样本的多态性数据。为该项目开发的新方法将使这些数据得到有效利用，并将提高研究人员检测疾病易感性的真实遗传效应并将其与统计噪音区分开来的能力。计算机程序将免费分发给更广泛的研究社区，以确保这些方法广泛而容易地应用于现实世界的问题。

The goals of this project are to develop improved quantitative methods for analysis of genetic data gathered in family and population studies of complex diseases, and to implement these methods in easy to use computer programs. Such methods are required to unravel the complex genetic basis of common diseases. New methods will be developed for the following tasks: Faster and more memory-efficient multi-point analysis of both qualitative and quantitative traits in arbitrarily large and complex pedigrees; Testing haplotypes for association with disease; Multipoint linkage disequilibrium analysis; SNP-based association studies. New technologies are allowing collection of increasingly large amounts of polymorphism data on common disease samples drawn from both families and populations. The new methods developed for this project will enable efficient use of these data, and will improve researchers' ability to detect true genetic effects on disease susceptibility and to distinguish them from statistical noise. The computer programs will be freely distributed to the broader research community to ensure that the methods are widely and readily applied to real-world problems.