Testing for association in case-control genome-wide association studies with shared controls
Testing for association in case-control genome-wide association studies with shared controls
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DOI：
10.1177/0962280212474061
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发表时间：
2016-04-01
影响因子：
2.3
通讯作者：
Ng, Hon Keung Tony
中科院分区：
文献类型：
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作者：
Chen, Zhongxue;Huang, Hanwen;Ng, Hon Keung Tony
讨论了多疾病和共享对照（SC）的全基因组关联研究（GWAS）的统计分析。分析这些研究数据的常用方法是将每种疾病与SC或包括其他疾病的合并对照进行比较。我们观察到，应用个体关联测试可能是有问题的，因为这些测试可能会在检测疾病与单核苷酸多态性或拷贝数变异之间的显著关联方面遭受功率损失。我们在这里提出了一个两阶段的程序，其中我们首先应用整体卡方检验的多种疾病与SC;如果整体测试被拒绝，然后使用卡方分区方法的个别测试将被应用到每种疾病对SC。一个真实的GWAS数据集与SC和Monte Carlo模拟研究表明，该方法是更有效的，比其他现有的方法分析数据，从GWAS与多种疾病和SC。
The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that applying individual association tests can be problematic because these tests may suffer from power loss in detecting significant associations between diseases and single-nucleotide polymorphism or copy number variant. We propose here a two-stage procedure wherein we first apply an overall chi-square test for multiple diseases with SCs; if the overall test is rejected, then individual tests using the chi-square partition method will be applied to each disease against SCs. A real GWAS data set with SCs and a Monte Carlo simulation study are used to demonstrate that the proposed method is more effective and preferable than other existing methods for analyzing data from GWASs with multiple diseases and SCs.