An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.
An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.
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DOI：
10.1177/0962280216647422
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发表时间：
2018-03
影响因子：
2.3
通讯作者：
Yang JJ
中科院分区：
文献类型：
--
作者：
Buu A;Williams LK;Yang JJ
我们提出了一种针对混合二元和连续表型的新的全基因组关联测试，该测试使用有效的数值方法来估计原假设下 Fisher 组合统计量的经验分布。我们的仿真研究表明，所提出的方法控制了 I 类错误率，并将其功效保持在排列方法的水平。更重要的是，该方法的计算效率远高于排列方法。模拟结果还表明，当遗传效应增加、次要等位基因频率增加以及响应之间的相关性降低时，测试的功效增加。对成瘾研究数据库的统计分析：遗传学和环境表明，所提出的结合多种表型的方法可以提高识别标记的能力，否则，使用边缘测试可能无法选择这些标记。
We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher’s combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.