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首页> 外文期刊>Genetic epidemiology. >X-Chromosome Genetic Association Test Accounting for X-Inactivation, Skewed X-Inactivation, and Escape from X-lnactivation
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X-Chromosome Genetic Association Test Accounting for X-Inactivation, Skewed X-Inactivation, and Escape from X-lnactivation

机译:X染色体遗传协会测试说明X灭活,偏斜X灭活和X灭活

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X-chromosome inactivation (XCI) is the process in which one of the two copies of the X-chromosome in females is randomly inactivated to achieve the dosage compensation of X-linked genes between males and females. That is, 50% of the cells have one allele inactive and the other 50% of the cells have the other allele inactive. However, studies have shown that skewed or nonrandom XCI is a biological plausibility wherein more than 75% of cells have the same allele inactive. Also, some of the X-chromosome genes escape XCI, i.e., both alleles are active in all cells. Current statistical tests for X-chromosome association studies can either account for random XCI (e.g., Clayton's approach) or escape from XCI (e.g., PLINK software). Because the true XCI process is unknown and differs across different regions on the X-chromosome, we proposed a unified approach of maximizing likelihood ratio over all biological possibilities: random XCI, skewed XCI, and escape from XCI. A permutation-based procedure was developed to assess the significance of the approach. We conducted simulation studies to compare the performance of the proposed approach with Clayton's approach and PLTNK regression. The results showed that the proposed approach has higher powers in the scenarios where XCI is skewed while losing some power in scenarios where XCI is random or XCI is escaped, with well-controlled type I errors. We also applied the approach to the X-chromosomal genetic association study of head and neck cancer.
机译:X染色体失活(XCI)是这样的过程,其中雌性X染色体的两个拷贝之一随机失活,以实现雄性和雌性之间X连锁基因的剂量补偿。也就是说,50%的细胞具有一个等位基因失活,而其他50%的细胞具有另一个等位基因失活。但是,研究表明,偏斜或非随机XCI是生物学上的合理性,其中超过75%的细胞具有相同的等位基因失活。而且,一些X染色体基因逃逸了XCI,即两个等位基因在所有细胞中均具有活性。当前用于X染色体关联研究的统计测试可以解释随机XCI(例如,Clayton方法)或逃避XCI(例如,PLINK软件)。因为真正的XCI过程是未知的,并且在X染色体的不同区域之间存在差异,所以我们提出了一种统一的方法,以最大化所有生物学可能性(随机XCI,偏斜XCI和逃避XCI)的似然比。开发了基于置换的程序来评估该方法的重要性。我们进行了仿真研究,以比较建议的方法与Clayton方法和PLTNK回归的性能。结果表明,所提出的方法在XCI偏斜的情况下具有更高的功效,而在XCI随机或XCI逃脱且I类错误得到良好控制的情况下,会失去一些功效。我们还将这种方法应用于头颈癌的X染色体遗传关联研究。

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