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Summary statistic analyses can mistake confounding bias for heritability

机译:摘要统计分析可以错误地将混乱的偏见误认为遗传性

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ABSTRACT Linkage disequilibrium SCore regression (LDSC) has become a popular approach to estimate confounding bias, heritability, and genetic correlation using only genome‐wide association study (GWAS) test statistics. SumHer is a newly introduced alternative with similar aims. We show using theory and simulations that both approaches fail to adequately account for confounding bias, even when the assumed heritability model is correct. Consequently, these methods may estimate heritability poorly if there was an inadequate adjustment for confounding in the original GWAS analysis. We also show that the choice of a summary statistic for use in LDSC or SumHer can have a large impact on resulting inferences. Further, covariate adjustments in the original GWAS can alter the target of heritability estimation, which can be problematic for test statistics from a meta‐analysis of GWAS with different covariate adjustments.
机译:摘要连锁不平衡评分回归(LDSC)已成为仅使用基因组关联研究(GWAS)测试统计数据来估计混淆偏差,遗传性和遗传相关的流行方法。 Sumher是一个新引进的替代方案,具有类似的目标。 我们使用理论和模拟显示,即使假设的遗传性模型是正确的,两种方法也无法充分地解释混淆偏差。 因此,如果在原始GWAS分析中对混淆的调整不足,这些方法可能估计遗传性差。 我们还表明,在LDSC或Sumher中使用的摘要统计信息可能会对产生的推论产生很大的影响。 此外,原始GWA中的协变量调整可以改变可遗传性估计的目标,这对于从GWA的META分析中测试统计数据可能是有问题的,具有不同的协变调整。

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