Minor allele frequency thresholds strongly affect population structure inference with genomic data sets
Minor allele frequency thresholds strongly affect population structure inference with genomic data sets
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DOI：
10.1111/1755-0998.12995
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发表时间：
2019-05-01
影响因子：
7.7
通讯作者：
Battey, C. J.
中科院分区：
文献类型：
--
作者：
Linck, Ethan;Battey, C. J.
在大的DNA序列数据集中最小化错误的一种常见方法是删除具有低于某个指定阈值的次要等位基因频率（MAF）的可变位点。虽然广泛，这一程序有可能改变下游人口的遗传推断，并已收到相对较少的严格分析。在这里，我们使用模拟和经验的单核苷酸多态性数据集，以证明MAF阈值对人口结构的推断的影响，往往是人口基因组数据分析的第一步。我们发现，基于模型的人口结构的推断是混淆时，单例包括在对齐，基于模型的和多变量分析推断不太明显的集群时，更严格的MAF截止。我们认为，这种行为是由数据矩阵的总大小下降和等位基因频率与突变年龄之间的相关性的组合引起的。我们推荐了一组在寻求用基因组数据描述种群结构的研究中应用MAF过滤器的最佳实践。
A common method of minimizing errors in large DNA sequence data sets is to drop variable sites with a minor allele frequency (MAF) below some specified threshold. Although widespread, this procedure has the potential to alter downstream population genetic inferences and has received relatively little rigorous analysis. Here we use simulations and an empirical single nucleotide polymorphism data set to demonstrate the impacts of MAF thresholds on inference of population structure-often the first step in analysis of population genomic data. We find that model-based inference of population structure is confounded when singletons are included in the alignment, and that both model-based and multivariate analyses infer less distinct clusters when more stringent MAF cutoffs are applied. We propose that this behaviour is caused by the combination of a drop in the total size of the data matrix and by correlations between allele frequencies and mutational age. We recommend a set of best practices for applying MAF filters in studies seeking to describe population structure with genomic data.