ESTIMATION & TEST OF MARKER ASSOCIATION IN FAMILY DATA

预估

• 批准号: 3470827
• 负责人: VARGHESE GEORGE
• 金额: $ 8.55万
• 依托单位: LSU HEALTH SCIENCES CENTER
• 依托单位国家: 美国
• 财政年份: 1988
• 资助国家: 美国
• 起止时间: 1988-09-28 至 1993-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3470827
• 关键词: biological polymorphism; computer data analysis; computer simulation; disease /disorder proneness /risk; gene expression; genetic disorder; genetic markers; genetic models; human age group; human population genetics; mathematical model; model design /development; molecular pathology; statistics /biometry

There is currently an ever-growing number of polymorphic genetic markers available for the study of marker association with human disease traits. Knowledge of such associations provides a basic for genetic counseling. Because the study of familial disease by segregation and linkage analyses requires the collection of data on family and pedigree members, it is becoming more and more necessary to infer marker associations from data that have been collected with these multiple purposes in mind. Therefore, comprehensive, rigorous and practical statistical methodologies will be developed for analyzing from extended human pedigree data the associations between genetic markers and traits characteristic of familial diseases. Separate methodologies for qualitative traits, qualitative traits, and traits with variable age of onset will be developed. In the case of quantitative traits, the usual assumption of normality will be relaxed. The models will allow for a flexible correlation structure among the pedigree individuals. The statistical properties such as the bias, consistency, power and robustness of the estimators and the likelihood ratio tests developed will be studied by mathematical analysis and computer simulations. Extensions to different types of ascertainments will be developed. The methods will be applied to analyse pedigree data obtained from various ongoing studies in order to be sure that the methods are relevant to real data.

目前有越来越多的多态性遗传 可用于研究标记物与人类相关性的标记物 疾病特征 对这种联系的了解提供了一个基本的 做遗传咨询 因为对家族性疾病的研究 分离和联系分析需要收集数据 对家庭和血统成员的影响， 有必要从已经被发现的数据中推断标记关联， 收集这些多个目的。 因此，我们认为， 全面、严格和实用的统计方法 将开发用于分析扩展的人类谱系数据 遗传标记与性状特征的关联 家族性疾病。 定性和定量分析的单独方法 特征、质量特征和发病年龄可变的特征 将被开发。 在数量性状的情况下，通常 正常的假设将被放宽。 这些模型将允许 系谱个体之间的灵活的相关结构。 统计特性，如偏倚、一致性、功效和 估计量的稳健性和似然比检验 将通过数学分析和计算机来研究 模拟 对不同类型的确定的扩展将 发展。 这些方法将被应用于家系资料的分析 从各种正在进行的研究中获得，以确保 方法与真实的数据相关。