Suppr超能文献

基于无共同机制模型的系统发生基因组学综合似然率。

Integrated likelihood for phylogenomics under a no-common-mechanism model.

机构信息

Department of Computer Science, Rice University, Houston, TX, USA.

出版信息

BMC Genomics. 2020 Apr 16;21(Suppl 2):219. doi: 10.1186/s12864-020-6608-y.

Abstract

BACKGROUND

Multi-locus species phylogeny inference is based on models of sequence evolution on gene trees as well as models of gene tree evolution within the branches of species phylogenies. Almost all statistical methods for this inference task assume a common mechanism across all loci as captured by a single value of each branch length of the species phylogeny.

RESULTS

In this paper, we pursue a "no common mechanism" (NCM) model, where every gene tree evolves according to its own parameters of the species phylogeny. Based on this model, we derive an analytically integrated likelihood of both species trees and networks given the gene trees of multiple loci under an NCM model. We demonstrate the performance of inference under this integrated likelihood on both simulated and biological data.

CONCLUSIONS

The model presented here will afford opportunities for exploring connections among various criteria for estimating species phylogenies from multiple, independent loci. Furthermore, further development of this model could potentially result in more efficient methods for searching the space of species phylogenies by focusing solely on the topology of the phylogeny.

摘要

背景

多基因座物种系统发育推断是基于基因树上的序列进化模型以及物种系统发育分支内的基因树进化模型。几乎所有用于推断任务的统计方法都假设所有基因座具有共同的机制,该机制由物种系统发育的每个分支长度的单个值来捕获。

结果

在本文中,我们追求一种“无共同机制”(NCM)模型,其中每个基因树都根据其自身的物种树参数进行演化。基于该模型,我们推导出了在 NCM 模型下,给定多个基因座的基因树后,物种树和网络的解析综合似然性。我们在模拟和生物数据上展示了在该综合似然性下进行推断的性能。

结论

本文提出的模型将为从多个独立基因座估计物种系统发育的各种标准之间的联系提供机会。此外,该模型的进一步发展可能会通过仅关注系统发育的拓扑结构,为搜索物种系统发育空间提供更有效的方法。

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