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Detection of Genotyping Errors and Pseudo-SNPs Via Deviations From Hardy-Weinberg Equilibrium

机译:通过与Hardy-Weinberg平衡的偏差检测基因分型错误和伪SNP

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摘要

Genotype error can greatly reduce the power of a genetic study. For family data, genotype error can be assessed by examining marker data for non-Mendelian inconsistencies, closely linked markers for double recombination events, and consistency of duplicate genotypes. For case-control data, duplicate samples are genotyped, and controls are tested for deviations from Hardy-Weinberg equilibrium (HWE). Duplicate samples can provide accurate estimates of genotyping error rates, unless systematic genotyping errors have occurred. Although genotyping errors can cause deviations from HWE, these deviations are usually small, and the power to detect them is low except for high rates of genotyping error and/or large sample sizes. An additional problem is that even when deviations from HWE are detected for marker loci, without additional experimentation it is not possible to unequivocally implicate genotyping error as the cause. The power and sample sizes necessary to detect deviations from HWE for single-nucleotide polymorphism (SNP) data are examined for a variety of genotyping error and pseudo-SNP models. For the majority of genotyping models examined, the power is poor to detect deviations from HWE. For example, for 1,000 controls, if an allele with a frequency of 0.1 fails to amplify for 28% of the heterozygous genotypes producing a sample error rate of 0.05, the power is 0.51 to detect a deviation from HWE at an alpha level of 0.05. On the other hand, the detection of deviations from HWE for pseudo-SNPs (paralogous and ectopic sequence variants) for the majority of models examined produces a power of >0.8 for sample sizes as small as 50 individuals.
机译:基因型错误会大大降低基因研究的能力。对于家族数据,可以通过检查非孟德尔不一致的标记数据,双重重组事件的紧密连锁标记以及重复基因型的一致性来评估基因型错误。对于病例对照数据,对重复样本进行基因分型,并测试对照与Hardy-Weinberg平衡(HWE)的偏差。重复样本可以提供基因分型错误率的准确估计值,除非发生系统的基因分型错误。尽管基因分型错误可能会导致与HWE发生偏差,但这些偏差通常很小,并且除非基因分型错误的发生率高和/或样本量大,否则检测它们的能力很低。另一个问题是,即使在没有其他实验的情况下,即使检测到标记基因座与HWE的偏离,也无法明确地暗示基因分型错误为原因。对于各种基因分型误差和伪SNP模型,检查了检测单核苷酸多态性(SNP)数据与HWE的偏离所必需的功效和样本大小。对于所研究的大多数基因分型模型,检测HWE偏差的能力很差。例如,对于1,000个对照,如果频率为0.1的等位基因不能扩增28%的杂合基因型,从而产生0.05的样本错误率,则功效为0.51,可以检测到α水平为0.05时与HWE的偏离。另一方面,对于大多数检查的模型,对于伪SNP(旁系和异位序列变体)从HWE的偏离检测对于小至50个人的样本量,其功效均大于0.8。

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