ANALYZE: Software for Joint Linkage and LD Analysis

描述（研究者摘要）：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 方法到数据集。在许多情况下，统计研究的重点是 开发，而忽略了向潜在用户交付方法。 最近，P1和同事们提出了一个统一的概念基础， “基于模型”和“无模型”的连锁和连锁不平衡（LD）分析 用于二分性状的遗传流行病学研究。该方法已 在许多实际应用中，PT在实践中使用，但可能非常 使用现有的软件包应用起来很麻烦， 更广泛的科学家社区可能希望申请 他们在实践中。为此，作为本申请的一部分，建议 开发和分发能够自动执行这些分析的软件 以简单直接的方式。通过创造强大的技术 （至少以最一般的形式）对那些没有实质性的人来说是可以获得的。 统计和计算培训，将提供一项重要服务， 基因作图者群体，以及那些试图在基因组中检测连锁和/或LD的人。 自己的数据集。此外，这种方法可以允许事后分析 基因分型错误，遗传标记图错误， 假设基因型-表型关系在所研究的位点。联合 多个基因的分析也将被纳入软件，通过 使用PT最近描述的统计模型。此外，本发明还 将开发软件包以模拟更真实的数据集， 使研究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。软件来模拟 人口中的基因序列将被提供，这样用户就可以 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，以及软件将被 用于模拟和确定人群的谱系， 共同遗传和环境病因学模型的条件 特征（定性和定量）。这些程序将作为 部分扩展的分析软件包将在本拟议开发 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.