Suppr超能文献

平衡突变-漂变模型中尺度化突变率的最大似然估计量。

Maximum likelihood estimators for scaled mutation rates in an equilibrium mutation-drift model.

作者信息

Vogl Claus, Mikula Lynette C, Burden Conrad J

机构信息

Department of Biomedical Sciences, Vetmeduni Vienna, Veterinärplatz 1, A-1210 Wien, Austria.

Centre for Biological Diversity, School of Biology, University of St. Andrews, St Andrews KY16 9TH, UK.

出版信息

Theor Popul Biol. 2020 Aug;134:106-118. doi: 10.1016/j.tpb.2020.06.001. Epub 2020 Jun 18.

Abstract

The stationary sampling distribution of a neutral decoupled Moran or Wright-Fisher diffusion with neutral mutations is known to first order for a general rate matrix with small but otherwise unconstrained mutation rates. Using this distribution as a starting point we derive results for maximum likelihood estimates of scaled mutation rates from site frequency data under three model assumptions: a twelve-parameter general rate matrix, a nine-parameter reversible rate matrix, and a six-parameter strand-symmetric rate matrix. The site frequency spectrum is assumed to be sampled from a fixed size population in equilibrium, and to consist of allele frequency data at a large number of unlinked sites evolving with a common mutation rate matrix without selective bias. We correct an error in a previous treatment of the same problem (Burden and Tang, 2017) affecting the estimators for the general and strand-symmetric rate matrices. The method is applied to a biological dataset consisting of a site frequency spectrum extracted from short autosomal introns in a sample of Drosophila melanogaster individuals.

摘要

对于具有中性突变的中性解耦莫兰(Moran)或赖特 - 费希尔(Wright-Fisher)扩散,其平稳抽样分布在突变率较小但无其他限制的一般速率矩阵下,已知到一阶近似。以该分布为起点,我们在三种模型假设下,从位点频率数据推导了缩放突变率的最大似然估计结果:一个十二参数的一般速率矩阵、一个九参数的可逆速率矩阵和一个六参数的链对称速率矩阵。假设位点频率谱是从处于平衡状态的固定大小群体中抽样得到的,并且由大量不连锁位点的等位基因频率数据组成,这些位点以共同的突变率矩阵进化且无选择偏差。我们纠正了先前处理同一问题(Burden和Tang,2017)中影响一般和链对称速率矩阵估计量的一个错误。该方法应用于一个生物学数据集,该数据集由从黑腹果蝇个体样本的短常染色体内含子中提取的位点频率谱组成。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验