Maximizing the Power of Genome-Wide Association Studies: A Novel Class of Powerful Family-Based Association Tests.
Maximizing the Power of Genome-Wide Association Studies: A Novel Class of Powerful Family-Based Association Tests.
复制标题
最大化全基因组关联研究的力量：一类新型的强大的基于家庭的关联测试。
DOI：
10.1007/s12561-009-9016-z
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发表时间：
2009
影响因子：
1
通讯作者：
Lange,Christoph
中科院分区：
文献类型：
--
作者：
Won,Sungho;Bertram,Lars;Becker,David;Tanzi,RudolphE;Lange,Christoph
对于基于家族的设计中的全基因组关联研究，提出了一种新的、普遍适用的方法。使用改进的Liptak方法，我们将基于家族的关联检验(FBAT)统计量的p值与Van Steen统计量的p值相结合。Van Steen统计量独立于FBAT统计量，并利用了传统FBAT方法忽略的信息。新的测试统计量利用了关于遗传关联的所有可用信息，同时，由于其设计，它实现了对由于种群分层而造成的混杂的完全稳健性。该方法适用于几乎所有可使用FBAT的性状类型的分析，如二元、连续、发病时间、多变量等。新方法的效率和有效性取决于改进的Liptak方法中的干扰/调谐参数和权重参数的指定。对于不同的性状类型和确定条件，我们讨论了调谐参数和权重参数的最优规范的一般准则。我们的模拟实验和在阿尔茨海默病研究中的应用表明了新方法的有效性和效率，它达到了与基于种群的方法相当的功率水平。
For genome-wide association studies in family-based designs, a new, universally applicable approach is proposed. Using a modified Liptak’s method, we combine thep-value of the family-based association test (FBAT) statistic with thep-value for the Van Steen-statistic. The Van Steen-statistic is independent of the FBAT-statistic and utilizes information that is ignored by traditional FBAT-approaches. The new test statistic takes advantages of all available information about the genetic association, while, by virtue of its design, it achieves complete robustness against confounding due to population stratification. The approach is suitable for the analysis of almost any trait type for which FBATs are available, e.g. binary, continuous, time-to-onset, multivariate, etc. The efficiency and the validity of the new approach depend on the specification of a nuisance/tuning parameter and the weight parameters in the modified Liptak’s method. For different trait types and ascertainment conditions, we discuss general guidelines for the optimal specification of the tuning parameter and the weight parameters. Our simulation experiments and an application to an Alzheimer study show the validity and the efficiency of the new method, which achieves power levels that are comparable to those of population-based approaches.