METHODS FOR MULTIPOINT ANALYSIS OF COMPLEX PHENOTYPES

我们之前开发了统计方法，旨在划分 数量性状的遗传变异对基因座效应的影响 特定的染色体区域(Goldgar1990)。此方法为 同一性模式对兄弟关系特征值协方差的影响 以及定义给定染色体的一组标记基因座的重组 区域。这种多点IBD方法(MIM)已初步显示 研究将比现有的方法更强大，这些方法基于 在同胞配对中，个体基因座的血统同一性。这些研究描述了 旨在进一步描述和扩展这一点 方法。具体来说，我们将使用蒙特卡罗 检验该方法对离差的稳健性的仿真技术 并将其能力和健壮性与 同胞配对和传统的依赖模型的连锁分析方法。 其他研究旨在将MIM方法扩展到分析 离散性状，如复杂的疾病表型与基因 敏感度。将对健壮性和功率进行类似的模拟研究 用于分析离散性状，如数量性状。 作为基因组计划的一部分，一组高度多态的索引标记 正在为每一条人类染色体研发。这件事的第二个方面 建议是通过模拟研究来确定最有效的 利用这些索引标记进行基因组搜索的策略 对于可能影响给定复杂表型的所有基因座。MIM方法 将在计算机程序中实现，以便于分析 分别收集的三个数据集中的几个表型 资助同时进行的研究。待分析的表型包括：一些 一组家庭中与认知能力相关的数量性状 被确定为阅读障碍；以及量化和离散 表型被认为是常见癌症的先兆。

We previously developed statistical methodology designed to partition the genetic variance of a quantitative trait to the effects of loci located in specific chromosomal regions (Goldgar 1990). This method models the covariance of sibship trait values as a function of the pattern of identity and recombination of a set of marker loci defining a given chromosomal region. This multipoint IBD method (MIM) has been shown in preliminary studies to be considerably more powerful than existing methods based upon identity by descent at individual loci in sib-pairs. The studies described in this proposal are designed to further characterize and extend this method in a number of ways. Specifically, we will use Monte-Carlo simulation techniques to examine the robustness of the method to departures from the underlying assumptions and to compare its power and robustness to both sib-pair and traditional model-dependent methods of linkage analysis. Other studies are designed to extend the MIM method to the analysis of discrete traits such as complex disease phenotypes with a genetic susceptibility. Similar simulation studies of robustness and power will be performed for the analysis of discrete traits as for quantitative traits. As part of the GENOME initiative, a set of highly polymorphic index markers is being developed for every human chromosome. A second aspect of this proposal is to determine through simulation studies the most efficient strategy for utilizing these index markers in conducting genomic searches for all loci which may influence a given complex phenotype. The MIM method will be implemented in a computer program to facilitate the analysis of several phenotypes in three data sets collected as part of separately funded concurrent studies. Phenotypes to be analyzed include: a number of quantitative traits related to cognitive abilities in a set of families ascertained for reading disability; and both quantitative and discrete phenotypes hypothesized to be precursors to common cancer.