Walters Kevin
Mathematical Modelling and Genetic Epidemiology Group, Division of Genomic Medicine, EU28, School of Medicine & Biomedical Sciences, Beech Hill Road, Sheffield, S10 2RX, UK.
J Hum Genet. 2005;50(7):329-337. doi: 10.1007/s10038-005-0269-1. Epub 2005 Jul 30.
In genomewide linkage scans for complex diseases involving many loci with small genetic effects, it may be the case that no loci reach conventional statistical significance. A complementary method of evaluating linkage results, locus counting, may provide evidence for the existence of a number of genetic loci in these cases. Sib-pair study designs are often used in genomewide linkage scans, but because all genotype configurations are consistent with Mendelian inheritance, genotyping error will go largely undetected. Previous work on the effect of genotyping error has focused on a single disease locus. We considered the effect of two levels of genotyping error on genomewide evidence for linkage by using the simulated GAW 13 data. For affected sib-pair and non-parametric quantitative trait study designs, a 0.5% genotyping error rate reduced the number of independent linkage regions towards that expected under the null hypothesis of no linkage. A 2% genotyping error rate yielded less independent linkage regions than expected under the null hypothesis of no linkage. For a quantitative trait analysed using a parametric regression-based method, there was very little erosion of the linkage signal, even for error rates as high as 2%.
在针对涉及多个具有微小遗传效应基因座的复杂疾病进行全基因组连锁扫描时，可能会出现没有基因座达到传统统计学显著性的情况。一种评估连锁结果的补充方法——基因座计数，在这些情况下可能会为多个遗传基因座的存在提供证据。同胞对研究设计常用于全基因组连锁扫描，但由于所有基因型配置都符合孟德尔遗传规律，基因分型错误在很大程度上会未被检测到。先前关于基因分型错误影响的研究主要集中在单个疾病基因座上。我们通过使用模拟的GAW 13数据，考虑了两个水平的基因分型错误对全基因组连锁证据的影响。对于患病同胞对和非参数数量性状研究设计，0.5%的基因分型错误率使独立连锁区域的数量向无连锁的零假设下预期的数量减少。2%的基因分型错误率产生的独立连锁区域比无连锁的零假设下预期的要少。对于使用基于参数回归方法分析的数量性状，即使错误率高达2%，连锁信号的减弱也非常小。
