Sum statistics for the joint detection of multiple disease loci in case-control association studies with SNP markers
Sum statistics for the joint detection of multiple disease loci in case-control association studies with SNP markers
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DOI：
10.1002/gepi.10263
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发表时间：
2003-12-01
影响因子：
2.1
通讯作者：
Ott, J
中科院分区：
文献类型：
--
作者：
Wille, A;Hoh, J;Ott, J
在复杂性状中，多个疾病位点可能相互作用产生疾病。由于这个原因，即使使用高分辨率的单核苷酸多态性（SNP）标记图谱，也难以通过常规的逐基因座方法绘制易感基因座。需要精细的定位策略，允许同时检测相互作用的疾病位点，同时处理大量密集间隔的标记。为此，总和统计最近被提出作为第一阶段的分析方法与SNPs的病例对照关联研究。通过单标志物统计的总和，组合多个疾病相关标志物的信息，并且利用全局显著性值α，选择一小组“感兴趣的”标志物用于进一步分析。在这里，这种方法的统计特性进行检查，通过计算机模拟。结果表明，总和统计往往可以成功地应用时，标记的标记方法无法检测关联。与Bonferroni或FDR方法相比，总和统计量具有更大的功效，并且可以检测到更多的疾病位点。然而，在紧密连锁标记的研究中，简单和统计可能是次优的，因为标记间的相关性被忽略了。提出了一种在标记统计量结合时考虑标记位点间相关结构的方法。(C)2003 Wiley-Liss，Inc.
In complex traits, multiple disease loci presumably interact to produce the disease. For this reason, even with high-resolution single nucleotide polymorphism (SNP) marker maps, it has been difficult to map susceptibility loci by conventional locus-by-locus methods. Fine mapping strategies are needed that allow for the simultaneous detection of interacting disease loci while handling large numbers of densely spaced markers. For this purpose, sum statistics were recently proposed as a first-stage analysis method for case-control association studies with SNPs. Via sums of single-marker statistics, information over multiple disease-associated markers is combined and, with a global significance value a, a small set of "interesting" markers is selected for further analysis. Here, the statistical properties of such approaches are examined by computer simulation. It is shown that sum statistics can often be successfully applied when marker-by-marker approaches fail to detect association. Compared with Bonferroni or False Discovery Rate (FDR) procedures, sum statistics have greater power, and more disease loci can be detected. However, in studies with tightly linked markers, simple sum statistics can be suboptimal, since the intermarker correlation is ignored. A method is presented that takes the correlation structure among marker loci into account when marker statistics are combined. (C) 2003 Wiley-Liss, Inc.