INFERENCE AND ROBUST METHODS FOR LINKAGE MAPPING

链接映射的推理和鲁棒方法

• 批准号: 6181404
• 负责人: Fred A. Wright
• 金额: $ 14.85万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-05-01 至 2003-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6181404
• 关键词: computer program /software; gene expression; genetic disorder; linkage mapping; mathematical model; method development; model design /development; quantitative trait loci; statistics /biometry

DESCRIPTION (Adapted from the Investigator's Abstract): In recent years, great methodological and computational advances have been made in genetic linkage mapping. However, several important tissues have received insufficient attention. The long-term objectives of this project are to develop new statistical and computational methods for discovering and localizing genes influencing complex traits and to improve the design of genetic linkage studies. All of the methods apply directly to experimental crosses and human studies involving relative pairs, and so are of immediate biomedical importance. In addition, the insight gathered from these investigations may enable extensions to more genetic epidemiological designs including the parametric analysis of multiplex pedigrees. The specific aims are: I. to develop general and flexible methods for constructing confidence intervals for gene locations in genetic linkage studies. A method proposed here is surprisingly simple and straightforward , and can be implemented immediately by researchers using existing software for multipoint mapping. II. to unify several linkage mapping approaches, to obtain an improved understanding of the connections among various genetic epidemiological designs. In addition, the unification appears to enable simple and powerful investigation of efficiency and precision of various linkage designs. III. to develop extremely general non-parametric approaches to linkage analysis of QTLS using empirical distribution functions of phenotypes conditioned of IBD status, and to develop adaptive pseudo-likelihood methods for efficient inference for the gene location. These aims will be achieved using both analytic and computational approaches, and any computer algorithms developed for this purpose will be distributed for public use. In addition, many of the methods proposed can be easily implemented by other investigators using existing software. The robustness and wide applicability of the methods proposed will be examined using a combination of simulation and analysis of existing linkage datasets.

描述（改编自研究者摘要）：近年来， 在遗传学研究中， 连锁作图然而，几个重要的组织已经收到了 注意力不足。该项目的长期目标是 开发新的统计和计算方法， 定位影响复杂性状的基因， 遗传连锁研究。所有的方法都直接适用于实验 交叉和人类研究涉及相对对，所以是 直接的生物医学意义。此外，从 这些研究可能使更多的遗传流行病学 设计包括多重家系的参数分析。 具体目标是：一。制定通用和灵活的方法， 遗传连锁中基因定位的置信区间构建 问题研究这里提出的一种方法是令人惊讶的简单和直接 ，研究人员可以立即使用现有的 多点映射软件。二.统一几个连锁图谱 方法，以更好地了解 各种遗传流行病学设计。此外，统一 似乎能够简单而有力地调查效率， 各种联动设计的精度。三.发展出非常普遍的 非参数方法的联系分析QTLS使用经验 以IBD状态为条件的表型分布函数，以及 开发自适应伪似然方法，用于有效推断 基因定位 这些目标将通过分析和计算来实现 方法，并且为此目的开发的任何计算机算法将是 分发给公众使用。此外，提出的许多方法可以 其他研究人员可以使用现有软件轻松实现。的 将检验所提出的方法的稳健性和广泛适用性 使用模拟和分析现有链接的组合 数据集。