ESTIMATION & TEST OF MARKER ASSOCIATION IN FAMILY DATA

预估

• 批准号: 3470826
• 负责人: VARGHESE GEORGE
• 金额: $ 8.11万
• 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 1993-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3470826
• 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，多态性遗传的数量不断增加。 可用于研究标记与人类关联的标记 疾病特征。 对此类协会的了解提供了基本的 用于遗传咨询。 因为对家族性疾病的研究 分离和连锁分析需要收集数据 在家庭和血统成员身上，它变得越来越多 有必要从已获得的数据推断标记关联 考虑到这些多重目的而收集。 所以， 全面、严谨、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之间的关联 的家族性疾病。 单独的定性方法 性状、质性状和发病年龄不同的性状 将被开发。 对于数量性状，通常 常态假设将被放宽。 这些模型将允许 谱系个体之间灵活的相关结构。 统计特性，例如偏差、一致性、功效和 估计量的稳健性和似然比检验 开发的将通过数学分析和计算机进行研究 模拟。 扩展至不同类型的查明将 得到开发。 该方法将用于分析谱系数据 从各种正在进行的研究中获得，以确保 方法与真实数据相关。