Department of Electrical and Electronic Engineering, Faculty of Engineering, Turgut Ozal University, 06010 Ankara, Turkey.
Comput Math Methods Med. 2013;2013:235825. doi: 10.1155/2013/235825. Epub 2013 May 2.
In family-based genetic association studies, it is possible to encounter missing genotype information for one of the parents. This leads to a study consisting of both case-parent trios and case-parent pairs. One of the approaches to this problem is permutation-based combined transmission disequilibrium test statistic. However, it is still unknown how powerful this test statistic is with small sample sizes. In this paper, a simulation study is carried out to estimate the power and false positive rate of this test across different sample sizes for a family-based genome-wide association study. It is observed that a statistical power of over 80% and a reasonable false positive rate estimate can be achieved even with a combination of 50 trios and 30 pairs when 2% of the SNPs are assumed to be associated. Moreover, even smaller samples provide high power when smaller percentages of SNPs are associated with the disease.
在基于家系的遗传关联研究中，有可能遇到父母一方的基因型信息缺失。这导致研究既有病例-父母三体型，也有病例-父母二体型。解决这个问题的方法之一是基于置换的联合传递不平衡检验统计量。然而，这种检验统计量在小样本量下的功效仍然未知。在本文中，进行了一项模拟研究，以估计在不同样本量下，基于家系的全基因组关联研究中，这种检验统计量的功效和假阳性率。结果表明，即使在假设 2%的 SNP 与疾病相关的情况下，结合 50 个三体型和 30 个二体型，也可以达到超过 80%的统计功效和合理的假阳性率估计。此外，当较小比例的 SNP 与疾病相关时，较小的样本量也能提供较高的功效。
