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

机译:评估非差异基因分型错误对关联的稀有变异测试的影响。

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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.
机译:背景/目的:我们旨在量化非差异基因分型错误对稀有变异测试功效的影响,并确定基因分型错误最有害的情况。方法:我们针对一系列样本量,次要等位基因频率,疾病相对风险和稀有变异数模拟了基因型和表型数据。然后使用涵盖了广泛错误率的五个不同错误模型来模拟基因型错误。结果:即使错误率非常低,将普通纯合子错误地分类为杂合子也将导致能量的大量损失,随着次要等位基因频率的降低,这一结果会进一步恶化。尽管对于给定的错误率,从杂合子到常见的纯合子错误的功率损失趋向于较小,但实际上杂合子到纯合子错误的损失更为频繁,因此对功率有可测量的影响。结论:从基因型调用技术获取的下一代测序数据的错误率表明,将当前罕见的关联变异测试应用于被称为基因型时,可能会看到大量的功率损耗。

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