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Fine-mapping using the weighted average method for a case-control study

机译:使用加权平均法进行精细映射以进行病例对照研究

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摘要

We present a new method for fine-mapping a disease susceptibility locus using a case-control design. The new method, termed the weighted average (WA) statistic, averages the Cochran-Armitage (CA) trend test statistic and the difference between the Hardy-Weinberg disequilibrium test statistic for cases and controls (the HWD trend). The main characteristics of the WA statistic are that it improves on the weaknesses, and maintains the strengths, of both the CA trend test and the HWD trend test. Data from three different populations in the Genetic Analysis Workshop 14 (GAW14) simulated dataset (Aipotu, Karangar, and Danacaa) were first subjected to model-free linkage analysis to find regions exhibiting linkage. Then, for fine-scale mapping, 140 SNPs within the significant linkage regions were analyzed with the WA test statistic on replicates of the three populations, both separately and combined. The regions that were significant in the multipoint linkage analysis were also significant in this fine-scale mapping. The most significant regions that were obtained using the WA statistic were regions in chromosome 3 (B03T3056–B03T3058, p-value < 1 × 10-10 ) and chromosome 9 (B09T8332–B09T8334, p-value 1 × 10-6 ). Based on the results of the simulated GAW14 data, the WA test statistic showed good performance and could narrow down the region containing the susceptibility locus. However, the strength of the signal depends on both the strength of the linkage disequilibrium and the heterozygosity of the linked marker.
机译:我们提出了一种使用病例对照设计精细映射疾病易感基因座的新方法。称为加权平均(WA)统计量的新方法将Cochran-Armitage(CA)趋势检验统计量与案例和对照的Hardy-Weinberg不平衡检验统计量之间的差异(HWD趋势)进行平均。 WA统计量的主要特征是,它可以改善CA趋势测试和HWD趋势测试的弱点,并保持优势。首先对“遗传分析研讨会14”(GAW14)模拟数据集中的三个不同种群的数据(Aipotu,Karangar和Danacaa)进行了无模型连锁分析,以发现表现出连锁的区域。然后,为了进行精细比例作图,对显着连锁区域内的140个SNP进行了WA检验统计,分别分析了三个种群的复制情况,并进行了组合。在多点链接分析中重要的区域在此精细比例映射中也很重要。使用WA统计量获得的最重要区域是3号染色体(B03T3056–B03T3058,p值<1×10 -10 )和9号染色体(B09T8332–B09T8334,p值1)中的区域。 ×10 -6 )。根据模拟的GAW14数据的结果,WA检验统计数据显示出良好的性能,并且可以缩小包含敏感性位点的区域。但是,信号强度取决于连锁不平衡的强度和连锁标记的杂合性。

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