METHODS FOR HUMAN GENETIC LINKAGE MAPPING

描述(改编自《调查员摘要》)：总体目标是 1.提供稳健的、在计算上可行的统计方法 分析遗传连锁数据，以及2.分析优势和 对现有方法的缺陷、改进和扩展。这些应该会进一步推动 定位与人类各种性状和基因相关的遗传基因座的目标 疾病，并确定它们的影响和遗传方式。特定的 目标如下： A.开发通过大规模等位基因共享来定位复杂性状的方法 血统。考虑选择最强大的分享统计数据。为 多点血统身份分享，就以下方面提出具体建议 下共享统计量和最强统计量的性质 某些假设。制定复杂性状精细定位的策略 在那些几乎完全独立的小的创始人群体中的基因 家谱信息，但这些信息太大，无法完全可行 多点分析。考虑按州和人口关联的身份 方法，并提出策略，以确定在 各种场景。 B.改进对遗传标记排序不确定度的评估 一种健壮而高效的方法，它不依赖于对 干扰。使用贝叶斯方法评估不确定性，组合数据 从不同的研究中，整合地图。 C.开发分析人类精子数据的方法和软件。 实施和改进检测偏析扭曲的程序， 建模干扰，并使用精子数据进行稳健的标记排序。使用 这些工具用于研究人类遗传参数的异质性 男性。 D.调查链接程序对以下问题的稳健性 错误指定的等位基因频率、基因分型错误和干扰。学习 不完整数据在加剧错误说明问题中的作用。精确定位 最令人关切的领域，制定诊断和补救措施。

DESCRIPTION (Adapted from the Investigator's Abstract): The broad goals are 1. to provide robust, computationally feasible statistical methods for analysis of genetic linkage data, and 2. to analyze the strengths and faults of, improve, and extend existing methods. These should further the goals of locating genetic loci involved in various human traits and diseases, and determine their effects and modes of inheritance. Specific aims are as follows: A. To develop methods for mapping complex traits by allele-sharing in large pedigrees. Consider selection of most powerful sharing statistics. For multipoint identity-by-descent sharing, make specific proposals regarding properties of such sharing statistics and most powerful statistics under certain assumptions. Develop strategies for fine mapping of complex trait genes in those small isolated founder populations with nearly complete genealogical information, but that are too large for feasible full multipoint analysis. Consider identity-by-state and population association methods and propose strategy to determine most powerful methods under a variety of scenarios. B. To improve assessment of uncertainty in ordering of genetic markers using a robust yet efficient method that does not rely on strong assumptions about interference. Use with Bayesian methods to assess uncertainty, combine data from different studies, integrate maps. C. To develop methods and software for analysis of human sperm data. Implement and improve programs for detecting segregation distortion, modeling interference, and for robust marker ordering with sperm data. Use these implementations to study heterogeneity of genetic parameters in human males. D. To investigate robustness of linkage procedures to problems such as misspecified allele frequencies, genotyping errors, and interference. Study role of incomplete data in exacerbating misspecification problems. Pinpoint areas of greatest concern, develop diagnostics and remedies.