Population genetic inference using a fixed number of segregating sites: a reassessment.

Sebastián E Ramos-Onsins, Sylvain Mousset, Thomas Mitchell-Olds, Wolfgang Stephan
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引用次数: 11

Abstract

Coalescent theory is commonly used to perform population genetic inference at the nucleotide level. Here, we examine the procedure that fixes the number of segregating sites (henceforth the FS procedure). In this approach a fixed number of segregating sites (S) are placed on a coalescent tree (independently of the total and internode lengths of the tree). Thus, although widely used, the FS procedure does not strictly follow the assumptions of coalescent theory and must be considered an approximation of (i) the standard procedure that uses a fixed population mutation parameter theta, and (ii) procedures that condition on the number of segregating sites. We study the differences in the false positive rate for nine statistics by comparing the FS procedure with the procedures (i) and (ii), using several evolutionary models with single-locus and multilocus data. Our results indicate that for single-locus data the FS procedure is accurate for the equilibrium neutral model, but problems arise under the alternative models studied; furthermore, for multilocus data, the FS procedure becomes inaccurate even for the standard neutral model. Therefore, we recommend a procedure that fixes the theta value (or alternatively, procedures that condition on S and take into account the uncertainty of theta) for analysing evolutionary models with multilocus data. With single-locus data, the FS procedure should not be employed for models other than the standard neutral model.

利用固定数量的分离位点进行群体遗传推断:重新评估。
聚结理论通常用于在核苷酸水平上进行群体遗传推断。在这里,我们研究确定分离位点数量的程序(今后称为FS程序)。在这种方法中,将固定数量的分离位点(S)放置在聚结树上(与树的总长度和节间长度无关)。因此,虽然被广泛使用,但FS程序并不严格遵循聚结理论的假设,必须被视为(i)使用固定种群突变参数theta的标准程序和(ii)以分离位点数量为条件的程序的近似。我们通过使用单位点和多位点数据的几种进化模型,将FS程序与程序(i)和(ii)进行比较,研究了9个统计量的假阳性率差异。结果表明,对于单基因座数据,FS程序对平衡中性模型是准确的,但在所研究的替代模型下存在问题;此外,对于多位点数据,FS程序即使对于标准中性模型也变得不准确。因此,我们推荐一种固定theta值的程序(或者,以S为条件并考虑theta的不确定性的程序)来分析具有多位点数据的进化模型。对于单基因座数据,除标准中性模型外,不应采用FS程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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