George Varghese, Laud Purushottam W
Department of Biostatistics, University of Alabama, 327N Ryals Public Health Building, 1665 University Boulevard, Birmingham, AL 35294-0022, USA.
Genet Epidemiol. 2002 Jan;22(1):41-51. doi: 10.1002/gepi.1042.
The transmission/disequilibrium test (TDT) for binary traits is a powerful method for detecting linkage between a marker locus and a trait locus in the presence of allelic association. The TDT uses information on the parent-to-offspring transmission status of the associated allele at the marker locus to assess linkage or association in the presence of the other, using one affected offspring from each set of parents. For testing for linkage in the presence of association, more than one offspring per family can be used. However, without incorporating the correlation structure among offspring, it is not possible to correctly assess the association in the presence of linkage. In this presentation, we propose a Bayesian TDT method as a complementary alternative to the classical approach. In the hypothesis testing setup, given two competing hypotheses, the Bayes factor can be used to weigh the evidence in favor of one of them, thus allowing us to decide between the two hypotheses using established criteria. We compare the proposed Bayesian TDT with a competing frequentist-testing method with respect to power and type I error validity. If we know the mode of inheritance of the disease, then the joint and marginal posterior distributions for the recombination fraction (theta) and disequilibrium coefficient (delta) can be obtained via standard MCMC methods, which lead naturally to Bayesian credible intervals for both parameters.
二元性状的传递/不平衡检验（TDT）是在存在等位基因关联的情况下检测标记位点与性状位点之间连锁的一种强大方法。TDT利用标记位点上相关等位基因的亲代到子代传递状态信息，在存在另一个等位基因的情况下评估连锁或关联，每组父母使用一个患病后代。为了在存在关联的情况下检验连锁，可以使用每个家庭不止一个后代。然而，如果不考虑后代之间的相关结构，就不可能在存在连锁的情况下正确评估关联。在本报告中，我们提出一种贝叶斯TDT方法作为经典方法的补充替代方法。在假设检验设置中，给定两个相互竞争的假设，贝叶斯因子可用于权衡支持其中一个假设的证据，从而使我们能够使用既定标准在两个假设之间做出决定。我们在检验功效和I型错误有效性方面，将所提出的贝叶斯TDT与一种竞争的频率检验方法进行比较。如果我们知道疾病的遗传模式，那么重组分数（θ）和不平衡系数（δ）的联合和边缘后验分布可以通过标准的马尔可夫链蒙特卡罗（MCMC）方法获得，这自然会得出两个参数的贝叶斯可信区间。
