An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.
An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.
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DOI：
10.1159/000457135
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发表时间：
2016
期刊：
影响因子：
1.8
通讯作者：
Heiman GA
中科院分区：
文献类型：
--
作者：
Gordon D;Londono D;Patel P;Kim W;Finch SJ;Heiman GA
我们在这里的动机是计算三个统计检验的权力时，有遗传性状的遗传多效性模式下运作，当定性表型定义的阈值的多个数量表型。具体来说，我们制定了一个多元函数，该函数提供了个体在具有风险基因座基因型的条件下具有特定数量性状值向量的概率，并且我们应用阈值来定义定性表型（受影响的、未受影响的），并计算外显率和条件基因型频率基于多元函数。我们扩展分析能力和最小样本量必要（MSSN）公式的两个分类为基础的测试（基因型，线性趋势检验（LTT））的遗传关联的多效性模型。我们进一步比较MSSN的基因型和LTT测试与MANOVA测试（Pillai）。我们使用析因设计和方差分析的线性模型近似MSSN的统计。通过ANOVA分解，我们确定哪些因素最显著地改变所有统计量的功效/MSSN。最后，我们确定哪些检验统计量具有最小的MSSN在这项工作中，MSSN计算仅针对两个性状（二元分布）（出于说明目的）。我们注意到，计算可以扩展到解决任何数量的性状。我们的主要发现是，基因型测试通常比LTT具有更小的MSSN要求。更具包容性的阈值（顶部/底部25%与顶部/底部10%）具有更高的样本量要求。由于样本选择，Pillai检验的MSSN比基因型和趋势检验大得多。有了这些公式，研究人员可以指定他们必须收集多少受试者来定位基因的多效性表型。
Our motivation here is to calculate the power of three statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected), and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend analytic power and minimum-sample-size-necessary (MSSN) formulas for two categorical-based tests (Genotype, Linear Trend Test (LTT)) of genetic association to the pleiotropic model. We further compare MSSN of the Genotype and LTT tests with that of a MANOVA test (Pillai). We approximate MSSN for statistics by linear models using factorial design and ANOVA. With the ANOVA decomposition, we determine what factors most significantly change power/MSSN for all statistics. Finally, we determine what test statistics have smallest MSSN In this work, MSSN calculations are for two traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the Genotype test usually has smaller MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% versus top/bottom 10%) have higher sample size requirements. The Pillai test has much larger MSSN than both the Genotype and Trend tests as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes.
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使用主要成分探索多效性。
影响因子：
2.9
作者：
Bensen, JT;Lange, LA;Langefeld, CD;Chang, BL;Bleecker, ER;Meyers, DA;Xu, JF
通讯作者：
Xu, JF
影响因子：
2.1
作者：
Bowden J;Davey Smith G;Haycock PC;Burgess S
通讯作者：
Burgess S
DOI：
10.1146/annurev-genom-090314-024956
发表时间：
2016-08-31
影响因子：
8.7
作者：
Denny JC;Bastarache L;Roden DM
通讯作者：
Roden DM
影响因子：
1.5
作者：
ALBIN, RL
通讯作者：
ALBIN, RL
DOI：
10.1007/978-1-4939-2155-3_14
发表时间：
2015-01-01
期刊：
EPISTASIS: METHODS AND PROTOCOLS
影响因子：
--
作者：
Darabos, Christian;Moore, Jason H.
通讯作者：
Moore, Jason H.