ANALYZE: Software for Joint Linkage and LD Analysis

描述(研究人员摘要)：统计学的两个重要方面 遗传学研究是新方法的发展和这种方法的应用 方法添加到数据集。在许多情况下，统计研究的重点是 开发，并忽略将方法交付给潜在用户。 最近，P1和他的同事们提出了统一的概念基础 “基于模型”和“无模型”链接和链接不平衡(LD)分析 用于二分性性状的遗传流行病学研究。这种方法一直是 在实践中使用的PT，在许多实际应用中，但可以非常 使用现有的软件包很难应用，这使得它们 可能希望申请的更广泛的科学家社区无法接触到 他们在实践中。为此，作为本申请的一部分，建议 开发和分发可自动执行这些分析的软件 以一种简单而直接的方式。通过制造强大的技术 (至少以其最一般的形式)对那些没有实质性 统计和计算培训，一项重要服务将提供给 基因映射者的社区，以及那些试图检测连锁和/或LD的人 他们自己的数据集。此外，这种方法还可以进行事后分析 基因分型中的错误、遗传标记图谱中的错误以及 在被研究的基因座上假定的基因-表型关系。接合 对多个基因的分析也将包含在软件中，通过 PT最近描述的统计模型的使用。另外， 将开发用于模拟更真实的数据集的软件包， 使调查人员能够更准确地预测成功的机会 在指定的研究设计中进行映射。用于模拟生物进化的软件 将提供种群中的基因序列，以便用户可以 评估关于总体参数的不同假设对 等位基因复杂性、基因多样性和LD水平，以及软件 为模拟和确定种群中的系谱而开发的， 共同遗传和环境病因学模式的条件 性状(质量和数量)。这些程序将作为以下形式分发 将在本计划中开发的扩展分析软件包的一部分 项目。

DESCRIPTION (Investigator's abstract): Two important aspects of statistical genetics research are development of new methods and application of such methods to datasets. In many cases, statistical research focuses on development, and ignores delivery of the methods to the potential users. Recently the P1 and colleagues have proposed a conceptual basis for unifying "model-based" and "model-free" linkage and linkage disequilibrium (LD) analysis for genetic epidemiology studies of dichotomous traits. The approach has been used in practice by the PT, in numerous practical applications, but can be very cumbersome to apply using the existing software packages, making them inaccessible to the broader community of scientists who might wish to apply them in practice. To this end, as part of this application, it is proposed to develop and distribute software which can automatically perform these analyses in a simple and straightforward manner. By making powerful techniques accessible (at least in their most general form) to those without substantial statistical and computing training, an important service will be provided to the community of gene mappers, and those trying to detect linkage and/or LD in their own datasets. Furthermore, such methods can allow for post-hoc analysis of errors in genotyping, errors in genetic marker maps, and errors in the assumed genotype-phenotype relationship at the locus under study. Joint analysis of multiple genes will also be incorporated in the software, through the use of statistical models recently described by the PT. Additionally, software packages will be developed for simulation of more realistic datasets, allowing investigators to more accurately predict the chance for successful mapping within a specified study design. Software to simulate the evolution of gene sequences in populations will be made available, such that users can evaluate the effects of different assumptions about population parameters on allelic complexity, gene diversity, and levels of LD, and software will be developed for simulation and ascertainment of pedigrees from populations, conditional on models of joint genetic and environmental etiology of common traits (qualitative and quantitative). These programs will be distributed as part of the expanded ANALYZE software package to be developed in this proposed project.