A consistent least-squares criterion for calibrating edge lengths in phylogenetic networks

Jingcheng Xu, Cécile Ané
{"title":"A consistent least-squares criterion for calibrating edge lengths in phylogenetic networks","authors":"Jingcheng Xu, Cécile Ané","doi":"arxiv-2407.19343","DOIUrl":null,"url":null,"abstract":"In phylogenetic networks, it is desirable to estimate edge lengths in\nsubstitutions per site or calendar time. Yet, there is a lack of scalable\nmethods that provide such estimates. Here we consider the problem of obtaining\nedge length estimates from genetic distances, in the presence of rate variation\nacross genes and lineages, when the network topology is known. We propose a\nnovel criterion based on least-squares that is both consistent and\ncomputationally tractable. The crux of our approach is to decompose the genetic\ndistances into two parts, one of which is invariant across displayed trees of\nthe network. The scaled genetic distances are then fitted to the invariant\npart, while the average scaled genetic distances are fitted to the\nnon-invariant part. We show that this criterion is consistent provided that\nthere exists a tree path between some pair of tips in the network, and that\nedge lengths in the network are identifiable from average distances. We also\nprovide a constrained variant of this criterion assuming a molecular clock,\nwhich can be used to obtain relative edge lengths in calendar time.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"42 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Populations and Evolution","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.19343","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In phylogenetic networks, it is desirable to estimate edge lengths in substitutions per site or calendar time. Yet, there is a lack of scalable methods that provide such estimates. Here we consider the problem of obtaining edge length estimates from genetic distances, in the presence of rate variation across genes and lineages, when the network topology is known. We propose a novel criterion based on least-squares that is both consistent and computationally tractable. The crux of our approach is to decompose the genetic distances into two parts, one of which is invariant across displayed trees of the network. The scaled genetic distances are then fitted to the invariant part, while the average scaled genetic distances are fitted to the non-invariant part. We show that this criterion is consistent provided that there exists a tree path between some pair of tips in the network, and that edge lengths in the network are identifiable from average distances. We also provide a constrained variant of this criterion assuming a molecular clock, which can be used to obtain relative edge lengths in calendar time.
用于校准系统发育网络边缘长度的一致最小二乘标准
在系统发育网络中,我们需要估算每个位点或历时的边缘长度(edge lengths insubstitutions)。然而,目前还缺乏可提供此类估计的可扩展方法。在此,我们考虑了在已知网络拓扑结构的情况下,在存在跨基因和世系的速率变异时,从遗传距离中获取边长估计值的问题。我们提出了一种基于最小二乘法的边长标准,这种标准既具有一致性,又在计算上易于操作。我们方法的关键在于将遗传距离分解成两部分,其中一部分在网络显示的树中是不变的。缩放遗传距离拟合到不变部分,而平均缩放遗传距离拟合到非不变部分。我们证明,只要网络中的某对树尖之间存在一条树路径,并且网络中的树枝长度可以通过平均距离识别,那么这个标准就是一致的。我们还提供了这一标准的受限变体,假定有一个分子钟,可用来获得日历时间中的相对边长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信