LINKAGE ANALYSIS AND MULTIPLE LOCI

本研究的目的是探讨有效的本地化和 通过连锁分析对主基因进行排序。 虽然新基因 映射方法和程序已经出现，重要的能力是 仍然缺乏，许多统计概念已经过时。 基因定位 可以分为两个阶段：1）将基因初始分配给 染色体区域，和2）指定基因顺序和图距的染色体区域， 与所有的标记物相匹配。 重要性和 这些阶段的效率不同。 在第一阶段，我们 检测疾病位点和间隔良好的高 多态性标记 预期LOD评分的三个位点评价， 实际LOD评分足够。 我们将研究显著性水平 三位点分析法在饱和图上的连锁检验。 为 精细映射，我们将计算预期的LOD得分和基因的LOD得分 多个loci的顺序。 我们还将建立以下方面的显著性水平： 订单比较。 初步LOD评分足以证明 从本地化战略转向建立秩序， 介绍了 作为计算预期LOD得分和LOD的工具集， 分数进行调查，将开发一个基于知识的专家系统 该系统将把这些工具与适当的数据库和规则结合起来。 该系统将是一个自动化工具，协助设计 实验，评估实验数据，并重新设计 根据初步结果进行实验。 因此， 在不久的将来可以进行连接实验 有效地

This research is designed to investigate the efficient localization and ordering of major genes through linkage analysis. Although new gene mapping methods and programs have emerged, significant capabilities are still lacking and many of the statistical concepts are dated. Gene mapping can be divided into two phases: 1) initial assignment of a gene to a chromosomal region, and 2) assignment of gene order and map distance of the disease locus to all of the markers. The issues of significance and efficiency are different for these phases. In the first phase, we are testing for linkage between the disease locus and well-spaced highly polymorphic markers. Three locus evaluation of expected LOD scores and actual LOD scores are sufficient. We will investigate significance levels of the three locus analysis for testing linkage on saturated maps. For fine mapping we will compute expected LOD scores and LOD scores for gene order with multiple loci. We will also establish significance levels for comparison of orders. The preliminary LOD scores sufficient to justify a switch in strategy from localization to establishing order will be described. As the set of tools for calculating expected LOD scores and LOD scores are investigated, a knowledge-based expert system will be developed which will integrate these tools with the appropriate databases and rules. The system will be an automated tool assisting in designing the experiments, evaluating data from the experiments, and redesigning the experiment in light of the preliminary results. Thus, the large number of linkage experiments carried out in the near future can be performed efficiently.