Detecting association using epistatic information
Detecting association using epistatic information
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DOI：
10.1002/gepi.20250
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发表时间：
2007-12-01
影响因子：
2.1
通讯作者：
Clayton, David
中科院分区：
文献类型：
--
作者：
Chapman, Juliet;Clayton, David
在检测因果遗传变异方面，遗传关联研究的成功率不如预期的，当声称这种变异时，频繁的未复制。已经假定了许多可能的原因，包括样本量不足和可能未观察到的分层。另一种可能性，以及本文的重点是上毒或基因 - 基因相互作用。尽管我们不太可能收集有关疾病机制的信息，但纯粹是基于数据，但有可能通过在我们的测试统计范围内允许上毒来提高我们的能力来检测效果。本文得出了适当的“综合”测试，用于检测因果基因座，从而可以进行许多可能的相互作用，并将这种测试的功能与通常的主要效应测试进行比较。这种方法与普遍使用的方法不同，例如Marchini等人。 [2005]，因为它同时测试了主要影响和相互作用，而不是单独进行相互作用。通过“综合”检验检验的替代假设是特定感兴趣的基因座是否对疾病状态有缘故或上学的影响，因此与该基因座的主要效应测试直接相当。该论文首先考虑了观察到假定的因果变异的直接情况，然后将这些想法扩展到间接情况，在该情况下，因果变体未被观察到，并且我们有一组TAG单核苷酸多态性（TAG SNP），代表了代表区域感兴趣的。顺便说一句，间接综合测试统计统计的推导导致了一种新颖的“间接相互作用的间接案例测试”。
Genetic association studies have been less successful than expected in detecting causal genetic variants, with frequent nonreplication when such variants are claimed. Numerous possible reasons have been postulated, including inadequate sample size and possible unobserved stratification. Another possibility, and the focus of this paper, is that of epistasis, or gene-gene interaction. Although unlikely that we may glean information about disease mechanism, based purely upon the data, it may be possible to increase our power to detect an effect by allowing for epistasis within our test statistic. This paper derives an appropriate "omnibus" test for detecting causal loci whist allowing for numerous possible interactions and compares the power of such a test with that of the usual main effects test. This approach dif fers from that commonly used, for example by Marchini et al. [2005], in that it tests simultaneously for main effects and interactions, rather than interactions alone. The alternative hypothesis being tested by the "omnibus" test is whether a particular locus of interest has an effect on disease status, either marginally or epistatically and is therefore directly comparable to the main effects test at that locus. The paper begins by considering the direct case, in which the putative causal variants are observed and then extends these ideas to the indirect case in which the causal variants are unobserved and we have a set of tag single nucleotide polymorphisms (tag SNPs) representing the regions of interest. In passing, the derivation of the indirect omnibus test statistic leads to a novel "indirect case-only test for interaction".