An almost infinite sites model

IF 1.2 4区 生物学 Q4 ECOLOGY Theoretical Population Biology Pub Date : 2024-10-23 DOI:10.1016/j.tpb.2024.10.001
Alejandra Avalos-Pacheco , Mathias C. Cronjäger , Paul A. Jenkins , Jotun Hein
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引用次数: 0

Abstract

Motivation:

A main challenge in molecular evolution is to find computationally efficient mutation models with flexible assumptions that properly reflect genetic variation. The infinite sites model assumes that each mutation event occurs at a site never previously mutant, i.e. it does not allow recurrent mutations. This is reasonable for low mutation rates and makes statistical inference much more tractable. However, recurrent mutations are common enough to be observable from genetic variation data, even in species with low per-site mutation rates such as humans. The finite sites model on the other hand allows for recurrent mutations but is computationally unfeasible to work with in most cases. In this work, we bridge these two approaches by developing a novel molecular evolution model, the almost infinite sites model, that both admits recurrent mutations and is tractable. We provide a recursive characterization of the likelihood of our proposed model under complete linkage and outline a parsimonious approximation scheme for computing it.

Results:

We show the usefulness of our model in simulated and human mitochondrial data. Our results show that the AISM, in combination with a constraint on the total number of mutation events, can recover accurate approximations to the maximum likelihood estimator of the mutation rate.

Availability and implementation:

An implementation of our model is freely available along with code for reproducing our computational experiments at https://github.com/Cronjaeger/almost-infinite-sites-recursions.
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几乎无限的场地模型
动机分子进化的一个主要挑战是找到计算效率高、假设灵活、能正确反映遗传变异的突变模型。无限位点模型假设每次突变都发生在一个以前从未发生过突变的位点上,即不允许重复突变。这对低突变率来说是合理的,也使统计推断更加容易。然而,重复突变非常普遍,即使在人类等每个位点突变率较低的物种中,也能从遗传变异数据中观察到。另一方面,有限位点模型允许发生重复突变,但在大多数情况下计算上不可行。在这项研究中,我们开发了一种新的分子进化模型--几乎无限位点模型,它既允许重复突变,又易于操作,从而在这两种方法之间架起了一座桥梁。我们提供了我们提出的模型在完全关联条件下的可能性递归特征,并概述了计算该可能性的简便近似方案:我们在模拟数据和人类线粒体数据中展示了我们的模型的实用性。我们的结果表明,AISM 与突变事件总数的约束相结合,可以恢复突变率最大似然估计值的精确近似值:我们免费提供模型的实现以及用于重现计算实验的代码,请访问 https://github.com/Cronjaeger/almost-infinite-sites-recursions。
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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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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