Genome-Wide Association Studies Using Haplotype Clustering with a New Haplotype Similarity
Genome-Wide Association Studies Using Haplotype Clustering with a New Haplotype Similarity
复制标题
使用具有新单倍型相似性的单倍型聚类进行全基因组关联研究
DOI：
10.1002/gepi.20521
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发表时间：
2010-09-01
影响因子：
2.1
通讯作者：
Guo, Jianhua
中科院分区：
文献类型：
--
作者：
Jin, Lina;Zhu, Wensheng;Guo, Jianhua
关联分析旨在研究遗传变异，旨在检测与可观察到的性状的遗传关联，这在理解疾病的遗传基础方面发挥了越来越大的作用。在这些方法中，基于单倍型的关联研究被认为具有显著的优势，特别是在病例对照研究中对罕见疾病的关联研究。然而，在对这些单倍型进行建模时，它们会受到罕见单倍型引起的统计问题的影响。幸运的是，单倍型集群提供了一个吸引人的解决方案。在本研究中，我们发展了一种新的适合于亲和繁殖的单倍型相似性的聚类算法，它能够很好地解释稀有的单倍型，从而控制自由度问题。新的相似性可以包含单倍型结构信息，这被认为可以增强识别遗传变异和疾病之间的联系的能力和高分辨率。我们的模拟研究表明，与分支单倍型聚类法CLADHC相比，该方法在检测疾病标记物相关性方面具有优势。我们还举例说明了我们的方法在囊性纤维化中的应用，它在精细标测中显示了相当准确的估计。吉内。埃皮米诺。2010年，34：633-641。(C)2010年Wiley-Liss公司
Association analysis, with the aim of investigating genetic variations, is designed to detect genetic associations with observable traits, which has played an increasing part in understanding the genetic basis of diseases. Among these methods, haplotype-based association studies are believed to possess prominent advantages, especially for the rare diseases in case-control studies. However, when modeling these haplotypes, they are subjected to statistical problems caused by rare haplotypes. Fortunately, haplotype clustering offers an appealing solution. In this research, we have developed a new befitting haplotype similarity for "affinity propagation'' clustering algorithm, which can account for the rare haplotypes primely, so as to control for the issue on degrees of freedom. The new similarity can incorporate haplotype structure information, which is believed to enhance the power and provide high resolution for identifying associations between genetic variants and disease. Our simulation studies show that the proposed approach offers merits in detecting disease-marker associations in comparison with the cladistic haplotype clustering method CLADHC. We also illustrate an application of our method to cystic fibrosis, which shows quite accurate estimates during fine mapping. Genet. Epidemiol. 34 : 633-641, 2010. (C) 2010 Wiley-Liss, Inc.