STATISTICAL METHODS FOR IDENTITY BY DESCENT MAPS

描述（改编自研究者摘要）：绘制人类 疾病易感基因可能是一系列步骤中的第一步， 更好的诊断测试和最终的战略， 控制疾病。 使用成对或其他小组的 作为绘制基因图谱的基本单位，具有相同特征的亲属具有很大的 当感兴趣的性状是遗传复杂的或具有低或低的遗传特性时， 年龄依赖性痴呆 研究的目的是提供 统计学方法，以帮助设计和分析这种基因定位 人类遗传学和实验遗传学的研究，特别是当 扫描整个基因组或其一部分以搜索相关的 基因. 提案中强调的问题的动机是 正在开发基因组错配扫描实验室技术 在帕特里克·O博士的实验室里布朗;但拟议的统计 这些想法与分析从任何高度 多态性，合理密集的遗传图谱，并可应用于离散或 数量性状 具体的长期目标如下：（1）开发通用方法 用于搜索基因组以通过以下方式鉴定富含同一性的区域： 因此可能含有影响以下性状的基因： 兴趣 (2)开发通用、灵活的多基因性状模型; 开发适合这些模型的统计技术。 统计 将通过数学分析和计算机模拟来建立模型。 实验数据的分析将有助于验证和完善 模型 该提案的显著特点是：（1）系统性 考虑到扫描标记分布在整个 （2）利用基因统计量之间的关系 映射问题和“变点问题”，这已经彻底 在最近的统计研究中。

DESCRIPTION (Adapted from the Investigator's Abstract): Mapping human disease susceptibility genes can be the first in a series of steps leading to better diagnostic tests and ultimately strategies for combating or controlling the disease. The use of pairs or other small groups of relatives who share a trait as the basic unit for mapping genes has great advantages when the trait of interest is genetically complex or has low or age-dependent penetrance. The aim of the proposed research is to provide statistical methods to aid in the design and analysis of such gene mapping studies in human genetics and in experimental genetics, particularly when the whole genome or a portion thereof is scanned to search for the relevant genes. The problems emphasized in the proposal are motivated by the laboratory technique of Genomic Mismatch Scanning which is under development in the laboratory of Dr. Patrick O. Brown; but the proposed statistical ideas are relevant to the analysis of data obtained from any highly polymorphic, reasonably dense genetic map and can be applied to discrete or quantitative traits. Specific long term goals are the following: (1) Develop general methodology for searching the genome to identify regions of enriched identity by descent, hence likely to contain genes affecting the trait or traits of interest. (2) Develop general, flexible models of multigenic traits; develop statistical techniques appropriate for those models. Statistical models will be developed by mathematical analysis and computer simulation. The analysis of experimental data will serve to validate and refine the models. The distinguishing features of the proposal are: (1) systematic consideration of the effect of scanning markers distributed throughout the genome and (2) exploitation of the relation between the statistics of gene mapping problems and of "change-point problems," which have been thoroughly studied in recent statistical research.