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Genomics and genome-wide association studies: an integrative approach to expression QTL mapping.

机译:基因组学和全基因组关联研究:表达QTL定位的整合方法。

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摘要

Expression QTL mapping by integrating genome-wide gene expression and genotype data is a promising approach to identifying functional genetic variation, but is hampered by the large number of multiple comparisons inherent in such studies. A novel approach to addressing multiple testing problems in genome-wide family-based association studies is screening candidate markers using heritability or conditional power. We apply these methods in settings in which microarray gene expression data are used as phenotypes, screening for SNPs near the expressed genes. We perform association analyses for phenotypes using a univariate approach. We also perform simulations on trios with large numbers of causal SNPs to determine the optimal number of markers to use in a screen. We demonstrate that our family-based screening approach performs well in the analysis of integrative genomic datasets and that screening using either heritability or conditional power produces similar, though not identical, results.
机译:通过整合全基因组基因表达和基因型数据进行表达QTL定位是鉴定功能遗传变异的一种有前途的方法,但由于此类研究固有的大量多重比较而受阻。解决基于基因组的全家族关联研究中的多个测试问题的新方法是使用遗传力或条件力筛选候选标记。我们在将微阵列基因表达数据用作表型的环境中应用这些方法,筛选表达基因附近的SNP。我们使用单变量方法对表型进行关联分析。我们还对具有大量因果SNP的三重奏执行模拟,以确定在屏幕中使用的最佳标记数。我们证明,基于家庭的筛查方法在综合基因组数据集的分析中表现良好,并且使用遗传性或有条件能力进行筛查可产生相似但不相同的结果。

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