Wang Chan, Sun Leiming, Zheng Haitao, Hu Yue-Qing
State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.
Department of Statistics, School of Mathematics, Southwest Jiaotong University, Sichuan, China.
J Hum Genet. 2016 Oct;61(10):851-860. doi: 10.1038/jhg.2016.63. Epub 2016 Jun 9.
With the advance of next-generation sequencing technology, the rare variants join the common ones in explaining more proportions of heritability. The coexistence of variants of common with rare, causal with neutral and deleterious with protective is a norm and should be appropriately addressed. Some existing methods suffer from low power when one or more forms of coexistence present, impeding their applications in practice. In this paper, for case-parent trios, pseudocontrols are constructed using the nontransmitted alleles of the parents. The Kullback-Leibler divergence is utilized to measure the difference between the distributions of variants in a genetic region for the affected children and pseudocontrols, and two nonparametric test statistics KLTT and cKLTT are proposed. Extensive simulations show that they are robust to the opposite directions of the causal variants and the amount of neutral variants, and have superiority over the existing methods when both rare and common variants are involved. Furthermore, their efficiency is demonstrated in the application to the data from Framingham Heart Study.
随着下一代测序技术的发展，罕见变异与常见变异一同在解释更多比例的遗传力方面发挥作用。常见变异与罕见变异、致病变异与中性变异、有害变异与保护性变异并存是常态，应予以适当应对。当存在一种或多种并存形式时，一些现有方法的功效较低，阻碍了它们在实际中的应用。在本文中，对于病例-父母三联体，利用父母未传递的等位基因构建伪对照。使用库尔贝克-莱布勒散度来衡量受影响儿童和伪对照在遗传区域中变异分布之间的差异，并提出了两个非参数检验统计量KLTT和cKLTT。大量模拟表明，它们对因果变异的相反方向和中性变异的数量具有稳健性，并且在涉及罕见变异和常见变异时比现有方法更具优势。此外，它们在应用于弗雷明汉心脏研究的数据时的效率也得到了证明。
