Karunarathna Charith B, Graham Jinko
Hum Hered. 2018;83(1):30-39. doi: 10.1159/000486854. Epub 2018 May 16.
Many methods can detect trait association with causal variants in candidate genomic regions; however, a comparison of their ability to localize causal variants is lacking. We extend a previous study of the detection abilities of these methods to a comparison of their localization abilities.
Through coalescent simulation, we compare several popular association methods. Cases and controls are sampled from a diploid population to mimic human studies. As benchmarks for comparison, we include two methods that cluster phenotypes on the true genealogical trees: a naive Mantel test considered previously in haploid populations and an extension that takes into account whether case haplotypes carry a causal variant. We first work through a simulated dataset to illustrate the methods. We then perform a simulation study to score the localization and detection properties.
In our simulations, the association signal was localized least precisely by the naive Mantel test and most precisely by its extension. Most other approaches had intermediate performance similar to the single-variant Fisher exact test.
Our results confirm earlier findings in haploid populations about potential gains in performance from genealogy-based approaches. They also highlight differences between haploid and diploid populations when localizing and detecting causal variants.
许多方法可检测候选基因组区域中性状与因果变异的关联;然而,缺乏对这些方法定位因果变异能力的比较。我们将先前关于这些方法检测能力的研究扩展至对其定位能力的比较。
通过合并模拟,我们比较了几种常用的关联方法。病例组和对照组从二倍体群体中抽样以模拟人类研究。作为比较的基准,我们纳入了两种在真实系谱树上对表型进行聚类的方法:一种是先前在单倍体群体中考虑的朴素曼特尔检验,另一种是考虑病例单倍型是否携带因果变异的扩展方法。我们首先通过一个模拟数据集来说明这些方法。然后进行模拟研究以评估定位和检测特性。
在我们的模拟中,朴素曼特尔检验对关联信号的定位最不准确,其扩展方法定位最准确。大多数其他方法的表现介于两者之间,类似于单变量费舍尔精确检验。
我们的结果证实了单倍体群体中早期关于基于系谱的方法在性能上可能有所提升的发现。它们还突出了单倍体和二倍体群体在定位和检测因果变异时的差异。