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首页> 美国卫生研究院文献>American Journal of Human Genetics >A Transmission/Disequilibrium Test That Allows for Genotyping Errors in the Analysis of Single-Nucleotide Polymorphism Data
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A Transmission/Disequilibrium Test That Allows for Genotyping Errors in the Analysis of Single-Nucleotide Polymorphism Data

机译：传输/不平衡测试允许在单核苷酸多态性数据分析中进行基因分型错误

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The present study assesses the effects of genotyping errors on the type I error rate of a particular transmission/disequilibrium test (TDTstd), which assumes that data are errorless, and introduces a new transmission/disequilibrium test (TDTae) that allows for random genotyping errors. We evaluate the type I error rate and power of the TDTae under a variety of simulations and perform a power comparison between the TDTstd and the TDTae, for errorless data. Both the TDTstd and the TDTae statistics are computed as two times a log-likelihood difference, and both are asymptotically distributed as χ2 with 1 df. Genotype data for trios are simulated under a null hypothesis and under an alternative (power) hypothesis. For each simulation, errors are introduced randomly via a computer algorithm with different probabilities (called “allelic error rates”). The TDTstd statistic is computed on all trios that show Mendelian consistency, whereas the TDTae statistic is computed on all trios. The results indicate that TDTstd shows a significant increase in type I error when applied to data in which inconsistent trios are removed. This type I error increases both with an increase in sample size and with an increase in the allelic error rates. TDTae always maintains correct type I error rates for the simulations considered. Factors affecting the power of the TDTae are discussed. Finally, the power of TDTstd is at least that of TDTae for simulations with errorless data. Because data are rarely error free, we recommend that researchers use methods, such as the TDTae, that allow for errors in genotype data.
机译：本研究评估基因分型错误对特定传输/不平衡测试（TDTstd）的I型错误率的影响，该假设假定数据无误，并引入了一种新的传输/不平衡测试（TDTae），该测试允许随机基因分型错误。 。我们在各种模拟下评估I型错误率和TDTae的功率，并针对无错误数据在TDTstd和TDTae之间进行功率比较。 TDTstd和TDTae统计量均被计算为对数似然差的两倍，并且都以1 df渐近分布为χ 2 。三重奏的基因型数据是在原假设和替代（功效）假设下进行模拟的。对于每个模拟，都会通过计算机算法以不同的概率（称为“等位基因错误率”）随机引入错误。 TDTstd统计信息是对显示孟德尔一致性的所有三项计算的，而TDTae统计信息是对所有三项统计的。结果表明，当将TDTstd应用于删除了不一致的三重奏的数据时，I型错误显着增加。这种I型错误会随着样本数量的增加和等位基因错误率的增加而增加。 TDTae对于所考虑的仿真始终保持正确的I类错误率。讨论了影响TDTae功率的因素。最后，对于无错误数据的仿真，TDTstd的功能至少是TDTae的功能。由于数据很少会出现错误，因此我们建议研究人员使用TDTae这样的方法，以允许基因型数据出现错误。

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