Transmission disequilibrium test (TDT) when only one parent is available: the 1-TDT.
Transmission disequilibrium test (TDT) when only one parent is available: the 1-TDT.
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DOI：
10.1093/oxfordjournals.aje.a009923
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发表时间：
1999-07
影响因子：
5
通讯作者：
F. Sun;W. Flanders;Quanhe Yang;M. Khoury
中科院分区：
文献类型：
--
作者：
F. Sun;W. Flanders;Quanhe Yang;M. Khoury
传递不平衡检验(TDT)是一种定位与复杂疾病相关的疾病基因突变的有用方法。TDT需要患者及其父母的基因分型。最近，Ewens和Spielman(Am J Hum Genet 1998；62：450-8)将TDT扩展到至少有一个受影响个体和一个未受影响个体的同胞，并设计了一种新的检验，称为同胞传递/不平衡检验(S-TDT)。S-TDT可应用于起病年龄较晚的疾病，如非胰岛素依赖型糖尿病、精神障碍和与衰老有关的疾病。对于某些疾病，可能比较容易获得父母一方的基因，因为另一方不能进行研究，或者他/她不合作。Curtis和Sham(Ann Hum Genet 1995；59：323-36)表明，如果在TDT中只使用杂合双亲和纯合子后代，则在传递某些等位基因时会引入偏见。在这篇文章中，作者提出了一种新的测试，1-TDT，利用受影响个体的基因类型和每个受影响个体只有一个可用的亲本来检测候选基因座和疾病基因座之间的连锁。在没有连锁或关联的零假设下，测试是没有偏见的。作者使用模拟和真实数据集验证了他们的测试。最后，它们展示了如何组合来自不同类型族的数据。
The transmission disequilibrium test (TDT) is a useful method to locate mutations linked to disease genes associated with complex diseases. TDT requires genotypes of affected individuals and their parents. Recently, Ewens and Spielman (Am J Hum Genet 1998;62:450-8) extended the TDT for use in sibships with at least one affected and one unaffected individual and devised a new test called the sib transmission/disequilibrium test (S-TDT). The S-TDT can be applied to diseases with late age at onset such as non-insulin-dependent diabetes mellitus, psychiatric disorders, and diseases related to aging. For some disorders, it might be relatively easy to obtain the genotype of one parent either because the other parent is not available for study or he/she is not cooperative. Curtis and Sham (Ann Hum Genet 1995;59:323-36) showed that bias in transmitting certain alleles is introduced if only heterozygous parents and homozygous offspring are used in the TDT. In this paper, the authors propose a new test, the 1-TDT, to detect linkage between a candidate locus and a disease locus using genotypes of affected individuals and only one available parent for each affected individual. The test is not biased under the null hypothesis of no linkage or association. The authors validate their test using both simulated and real data sets. Finally, they show how to combine data from different types of families.