The use of haplotype information in case-control studies is an area of focus for the research on the association between phenotypes and genetic polymorphisms. We examined the validity of the application of the likelihood-based algorithm, which was originally developed to analyze the data from cohort studies or clinical trials, to the data from case-control studies. This algorithm was implemented in a computer program called PENHAPLO. In this program, haplotype frequencies and penetrances are estimated using the expectation-maximization algorithm, and the haplotype-phenotype association is tested using the generalized likelihood ratio. We show that this algorithm was useful not only for cohort studies but also for case-control studies. Simulations under the null hypothesis (no association between haplotypes and phenotypes) have shown that the type I error rates were accurately estimated. The simulations under alternative hypotheses showed that PENHAPLO is a robust method for the analysis of the data from case-control studies even when the haplotypes were not in HWE, although real penetrances cannot be estimated. The power of PENHAPLO was higher than that of other methods using the likelihood-ratio test for the comparison of haplotype frequencies. Results of the analysis of real data indicated that a significant association between haplotypes in the SAA1 gene and AA-amyloidosis phenotype was observed in patients with rheumatoid arthritis, thereby suggesting the validity of the application of PENHAPLO for case-control data.

译文

在病例对照研究中使用单倍型信息是研究表型与遗传多态性之间关联的重点领域。我们检查了基于可能性的算法的应用的有效性,该算法最初是为分析来自队列研究或临床试验的数据而开发的,以及来自病例对照研究的数据。此算法是在称为PENHAPLO的计算机程序中实现的。在该程序中,使用期望最大化算法估计单倍型频率和渗透率,并使用广义似然比测试单倍型-表型关联。我们证明了该算法不仅对队列研究有用,而且对病例对照研究也很有用。在零假设下的模拟 (单倍型和表型之间没有关联) 表明,I型错误率是准确估计的。在替代假设下的模拟表明,即使单倍型不在HWE中,PENHAPLO也是分析病例对照研究数据的可靠方法,尽管无法估计实际的渗透率。使用似然比检验比较单倍型频率,PENHAPLO的能力高于其他方法。对真实数据的分析结果表明,在类风湿关节炎患者中观察到SAA1基因的单倍型与AA-淀粉样变表型之间存在显着关联,从而表明PENHAPLO在病例对照数据中的应用是有效的。

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