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评估非差异性基因分型错误对罕见变异关联测试的影响。

Assessing the impact of non-differential genotyping errors on rare variant tests of association.

作者信息

Powers Scott, Gopalakrishnan Shyam, Tintle Nathan

机构信息

Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.

出版信息

Hum Hered. 2011;72(3):153-60. doi: 10.1159/000332222. Epub 2011 Oct 15.

Abstract

BACKGROUND/AIMS: We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful.

METHODS

We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates.

RESULTS

Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor allele frequency decreases. While the power loss from heterozygote to common homozygote errors tends to be smaller for a given error rate, in practice heterozygote to homozygote errors are more frequent and, thus, will have measurable impact on power.

CONCLUSION

Error rates from genotype-calling technology for next-generation sequencing data suggest that substantial power loss may be seen when applying current rare variant tests of association to called genotypes.

摘要

背景/目的:我们旨在量化非差异性基因分型错误对罕见变异检测效能的影响,并确定基因分型错误最具危害性的情况。

方法

我们针对一系列样本量、次要等位基因频率、疾病相对风险和罕见变异数量模拟了基因型和表型数据。然后使用涵盖广泛错误率的五种不同错误模型模拟基因分型错误。

结果

即使在非常低的错误率下,将常见纯合子误分类为杂合子也会导致效能大幅损失,随着次要等位基因频率降低,这一结果会进一步加剧。对于给定的错误率,从杂合子到常见纯合子错误导致的效能损失往往较小,但在实际中,从杂合子到纯合子的错误更为频繁,因此会对效能产生可测量的影响。

结论

下一代测序数据的基因分型技术的错误率表明,在将当前罕见变异关联检测应用于已分型的基因型时,可能会出现显著的效能损失。

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