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A Coalescent-Based Approach for Complex Disease Mapping

机译:基于联盟的复杂疾病映射方法

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摘要

There is currently great interest in the genetics community in identifying the genes that are involved in complex (multifactorial) diseases. One standard approach uses family-based "linkage" methods to identify regions of the genome that harbor susceptibility genes, and then population-based "linkage-disequilibrium" (LD) methods to search more narrowly for the culprit genes. Many of the important statistical issues involved in the first phase of this process, linkage mapping, have been addressed, but data analysis for LD-mapping remains extremely challenging. In this article we describe our work on developing a full statistical framework for LD mapping based on a population genetics model known as the coalescent.
机译:当前,遗传学界对鉴定涉及复杂(多因素)疾病的基因非常感兴趣。一种标准方法是使用基于家族的“连锁”方法来鉴定具有易感基因的基因组区域,然后使用基于群体的“连锁不平衡”(LD)方法来更窄地搜索罪魁祸首基因。已经解决了此过程的第一阶段中涉及的许多重要统计问题,即链接映射,但是用于LD映射的数据分析仍然极具挑战性。在本文中,我们描述了我们在基于人口遗传模型(称为合并)的LD映射的完整统计框架的开发工作。

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