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A comment on two-locus epistatic interaction models for genome-wide association studies

机译:用于全基因组关联研究的两基因座上位性相互作用模型的评论

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摘要

Detection of epistatic interactions in genome-wide association studies is a computationally hard problem. Many detection algorithms have been proposed and will continue to be. Most of those algorithms measure their predictive power by running on simulated data many times under various disease models. However, we find that there have been subtle differences in interpreting the meaning of existing disease models among the previous studies on detection of epistatic interactions. We elucidate those differences and suggest that future studies on epistatic interactions in GWAS state explicitly which versions/interpretations are employed. We also provide a way to facilitate setting parameters of disease models.
机译:全基因组关联研究中上位相互作用的检测是一个计算难题。已经提出了许多检测算法,并将继续存在。大多数这些算法通过在各种疾病模型下多次运行模拟数据来衡量其预测能力。然而,我们发现在对上位相互作用的检测的先前研究之间,在解释现有疾病模型的含义方面存在细微的差异。我们阐明了这些差异,并建议对GWAS中上位相互作用的未来研究明确指出采用了哪种版本/解释。我们还提供了一种方便设置疾病模型参数的方法。

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