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Two-phase SSU and SKAT in genetic association studies

机译:遗传关联研究中的两阶段SSU和SKAT

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The sum of squared score (SSU) and sequence kernel association test (SKAT) are the two good alternative tests for genetic association studies in casea??control data. Both SSU and SKAT are derived through assuming a dose-response model between the risk of disease and genotypes. However, in practice, the real genetic mode of inheritance is impossible to know. Thus, these two tests might losepower substantially as shown in simulation results when the genetic model is misspecified. Here, to make both the tests suitable in broad situations, we propose two-phase SSU (tpSSU) and two-phase SKAT (tpSKAT), where the Hardya??Weinberg equilibrium test is adopted to choose the genetic model in the first phase and the SSU and SKAT are constructed corresponding to the selected genetic model in the second phase. We found that both tpSSU and tpSKAT outperformed the original SSU and SKAT in most of our simulation scenarios. Byapplying tpSSU and tpSKAT to the study of type 2 diabetes data, we successfully identified some genes that have direct effects on obesity. Besides, we also detected the significant chromosomal region 10q21.22 in GAW16 rheumatoid arthritis dataset, with P10-6. These findings suggest that tpSSU and tpSKAT can be effective in identifying genetic variants for complex diseases in casea??control association studies.
机译:平方分(SSU)和序列核关联测试(SKAT)的总和是Casea的遗传关联研究的两个良好替代测试控制数据。 SSU和SKAT都是通过假设疾病和基因型风险之间的剂量响应模型来源的。然而,在实践中,遗传的真实遗传模式是不可能知道的。因此,当遗传模型被误操作时,这两个测试可能会使仿真结果中的模拟结果中所示。在这里,为了使这两个都适用于广泛的情况,我们提出了两阶段SSU(TPSSU)和两相滑雪(TPSKAT),其中采用了Hardya的Weinberg均衡测试来选择第一阶段的遗传模型SSU和SKAT对应于第二阶段的所选遗传模型构建。我们发现TPSSU和TPSKAT都在大多数模拟场景中表现出原始的SSU和SKAT。用TPSSU和TPSKAT对2型糖尿病数据的研究,我们成功地确定了对肥胖有直接影响的一些基因。此外,我们还在GAW16类风湿性关节炎数据集中检测到显着的染色体区域10Q21.22,P <10-6。这些研究结果表明,TPSSU和TPSKAT可以有效地识别卡西亚的复杂疾病的遗传变异性控制协会研究。

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