On the use of general control samples for genome-wide association studies: Genetic matching highlights causal variants
On the use of general control samples for genome-wide association studies: Genetic matching highlights causal variants
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DOI：
10.1016/j.ajhg.2007.11.003
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发表时间：
2008-02-01
影响因子：
9.8
通讯作者：
Trucco, Massimo
中科院分区：
文献类型：
--
作者：
Luca, Diana;Ringquist, Steven;Trucco, Massimo
为全基因组关联（GWA）研究积累的资源包括用大规模SNP阵列进行基因分型的“对照数据库”。如何有效地利用这些数据库是一个悬而未决的问题。我们开发了一种方法来匹配，遗传血统，控制受影响的个人（案件）。这种方法的影响，特别是对于异质人群，是降低假阳性率，夸大其他虚假的小p值，并对与真阳性基因座相关的p值几乎没有影响。因此，它通过淡化假阳性来突出真阳性。我们通过将患有I型糖尿病（T1D）的美国人与来自德国的对照组进行GWA。尽管研究设计复杂，但这些分析确定了许多已知会导致T1D风险的基因座。
Resources being amassed for genome-wide association (GWA) studies include "control databases" genotyped with a large-scale SNP array. How to use these databases effectively is an open question. We develop a method to match, by genetic ancestry, controls to affected individuals (cases). The impact of this method, especially for heterogeneous human populations, is to reduce the false-positive rate, inflate other spuriously small p values, and have little impact on the p values associated with true positive loci. Thus, it highlights true positives by downplaying false positives. We perform a GWA by matching Americans with type I diabetes (T1D) to controls from Germany. Despite the complex study design, these analyses identify numerous loci known to confer risk for T1D.