• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

在不同但相互重叠的分类单元集上定义的系统发育树的比较:综述。

Comparison of phylogenetic trees defined on different but mutually overlapping sets of taxa: A review.

作者信息

Li Wanlin, Koshkarov Aleksandr, Tahiri Nadia

机构信息

Department of Computer Science University of Sherbrooke Sherbrooke Quebec Canada.

出版信息

Ecol Evol. 2024 Aug 8;14(8):e70054. doi: 10.1002/ece3.70054. eCollection 2024 Aug.

DOI:10.1002/ece3.70054
PMID:39119174
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11307105/
Abstract

Phylogenetic trees represent the evolutionary relationships and ancestry of various species or groups of organisms. Comparing these trees by measuring the distance between them is essential for applications such as tree clustering and the Tree of Life project. Many distance metrics for phylogenetic trees focus on trees defined on the same set of taxa. However, some problems require calculating distances between trees with different but overlapping sets of taxa. This study reviews state-of-the-art distance measures for such trees, covering six major approaches, including the constraint-based Robinson-Foulds (RF) distance RF(-), the completion-based RF(+), the generalized RF (GRF), the dissimilarity measure, the vectorial tree distance, and the geodesic distance in the extended Billera-Holmes-Vogtmann tree space. Among these, three RF-based methods, RF(-), RF(+), and GRF, were examined in detail on generated clusters of phylogenetic trees defined on different but mutually overlapping sets of taxa. Additionally, we reviewed nine related techniques, including leaf imputation methods, the tree edit distance, and visual comparison. A comparison of the related distance measures, highlighting their principal advantages and shortcomings, is provided. This review offers valuable insights into their applicability and performance, guiding the appropriate use of these metrics based on tree type (rooted or unrooted) and information type (topological or branch lengths).

摘要

系统发育树代表了各种物种或生物群体的进化关系和祖先。通过测量它们之间的距离来比较这些树对于诸如树聚类和生命之树项目等应用至关重要。许多系统发育树的距离度量都集中在定义在同一分类单元集上的树。然而,一些问题需要计算具有不同但重叠分类单元集的树之间的距离。本研究回顾了针对此类树的最新距离度量方法,涵盖六种主要方法,包括基于约束的罗宾逊-福尔兹(RF)距离RF(-)、基于完备化的RF(+)、广义RF(GRF)、差异度量、向量树距离以及扩展的比勒拉-霍姆斯-沃格特曼树空间中的测地距离。其中,基于RF的三种方法,RF(-)、RF(+)和GRF,在定义于不同但相互重叠的分类单元集上生成的系统发育树聚类上进行了详细研究。此外,我们还回顾了九种相关技术,包括叶插补方法、树编辑距离和可视化比较。提供了相关距离度量的比较,突出了它们的主要优点和缺点。本综述为它们的适用性和性能提供了有价值的见解,根据树的类型(有根或无根)和信息类型(拓扑或分支长度)指导这些度量的适当使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/69471a627a08/ECE3-14-e70054-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/9b50ea902a52/ECE3-14-e70054-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/0290f29cc702/ECE3-14-e70054-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/6188218022bc/ECE3-14-e70054-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/d8f5793295c0/ECE3-14-e70054-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/070f4a8a23b8/ECE3-14-e70054-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/69471a627a08/ECE3-14-e70054-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/9b50ea902a52/ECE3-14-e70054-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/0290f29cc702/ECE3-14-e70054-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/6188218022bc/ECE3-14-e70054-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/d8f5793295c0/ECE3-14-e70054-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/070f4a8a23b8/ECE3-14-e70054-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cce/11307105/69471a627a08/ECE3-14-e70054-g006.jpg

相似文献

1
Comparison of phylogenetic trees defined on different but mutually overlapping sets of taxa: A review.在不同但相互重叠的分类单元集上定义的系统发育树的比较:综述。
Ecol Evol. 2024 Aug 8;14(8):e70054. doi: 10.1002/ece3.70054. eCollection 2024 Aug.
2
Invariant transformers of Robinson and Foulds distance matrices for Convolutional Neural Network.不变的 Robinson 和 Foulds 距离矩阵变换用于卷积神经网络。
J Bioinform Comput Biol. 2022 Aug;20(4):2250012. doi: 10.1142/S0219720022500123. Epub 2022 Jul 6.
3
The Generalized Robinson-Foulds Distance for Phylogenetic Trees.系统发育树的广义 Robinson-Foulds 距离。
J Comput Biol. 2021 Dec;28(12):1181-1195. doi: 10.1089/cmb.2021.0342. Epub 2021 Oct 29.
4
Linear-time algorithms for phylogenetic tree completion under Robinson-Foulds distance.基于罗宾逊-福尔兹距离的系统发育树补全的线性时间算法。
Algorithms Mol Biol. 2020 Apr 13;15:6. doi: 10.1186/s13015-020-00166-1. eCollection 2020.
5
Robinson-Foulds supertrees.罗宾逊-福尔兹超树
Algorithms Mol Biol. 2010 Feb 24;5:18. doi: 10.1186/1748-7188-5-18.
6
Fast local search for unrooted Robinson-Foulds supertrees.无根 Robinson-Foulds 超级树的快速局部搜索。
IEEE/ACM Trans Comput Biol Bioinform. 2012 Jul-Aug;9(4):1004-13. doi: 10.1109/TCBB.2012.47.
7
A Linear Time Solution to the Labeled Robinson-Foulds Distance Problem.线性时间解决带标签的罗宾逊-福尔德斯距离问题。
Syst Biol. 2022 Oct 12;71(6):1391-1403. doi: 10.1093/sysbio/syac028.
8
Inferring species trees from incongruent multi-copy gene trees using the Robinson-Foulds distance.使用罗宾逊-福尔兹距离从不一致的多拷贝基因树推断物种树。
Algorithms Mol Biol. 2013 Nov 1;8(1):28. doi: 10.1186/1748-7188-8-28.
9
The -Robinson-Foulds Dissimilarity Measures for Comparison of Labeled Trees.
J Comput Biol. 2024 Apr;31(4):328-344. doi: 10.1089/cmb.2023.0312. Epub 2024 Jan 25.
10
A strict upper bound for the partition distance and the cluster distance of phylogenetic trees for each fixed pair of topological trees.对每一对拓扑树固定的系统发育树的分区距离和聚类距离的严格上限。
PLoS One. 2018 Sep 28;13(9):e0204907. doi: 10.1371/journal.pone.0204907. eCollection 2018.

引用本文的文献

1
Distances Between Extension Spaces of Phylogenetic Trees.系统发育树扩展空间之间的距离。
IEEE Trans Comput Biol Bioinform. 2025 Mar-Apr;22(2):614-627. doi: 10.1109/TCBBIO.2025.3526422.

本文引用的文献

1
GPTree Cluster: phylogenetic tree cluster generator in the context of supertree inference.GPTree 聚类:超级树推断背景下的系统发育树聚类生成器。
Bioinform Adv. 2023 Mar 3;3(1):vbad023. doi: 10.1093/bioadv/vbad023. eCollection 2023.
2
Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data.基于四重奏的深度学习基因树推断在存在缺失数据的情况下仍能改进系统发育基因组分析。
J Comput Biol. 2022 Nov;29(11):1156-1172. doi: 10.1089/cmb.2022.0212. Epub 2022 Sep 1.
3
Building alternative consensus trees and supertrees using k-means and Robinson and Foulds distance.
使用 K-均值和罗宾逊-福尔德斯距离构建替代共识树和超级树。
Bioinformatics. 2022 Jun 27;38(13):3367-3376. doi: 10.1093/bioinformatics/btac326.
4
A vectorial tree distance measure.一种有向树距离度量。
Sci Rep. 2022 Mar 28;12(1):5256. doi: 10.1038/s41598-022-08360-4.
5
Comparing Phylogenetic Trees Side by Side Through iPhyloC, a New Interactive Web-Based Framework.通过iPhyloC(一个基于网络的新型交互式框架)并排比较系统发育树。
J Comput Biol. 2022 Mar;29(3):292-303. doi: 10.1089/cmb.2021.0351. Epub 2022 Feb 25.
6
Completing gene trees without species trees in sub-quadratic time.在亚二次时间内不依赖物种树完成基因树构建。
Bioinformatics. 2022 Mar 4;38(6):1532-1541. doi: 10.1093/bioinformatics/btab875.
7
The Generalized Robinson-Foulds Distance for Phylogenetic Trees.系统发育树的广义 Robinson-Foulds 距离。
J Comput Biol. 2021 Dec;28(12):1181-1195. doi: 10.1089/cmb.2021.0342. Epub 2021 Oct 29.
8
On Defining and Finding Islands of Trees and Mitigating Large Island Bias.定义和寻找树岛并减轻大岛偏差
Syst Biol. 2021 Oct 13;70(6):1282-1294. doi: 10.1093/sysbio/syab015.
9
Linear-time algorithms for phylogenetic tree completion under Robinson-Foulds distance.基于罗宾逊-福尔兹距离的系统发育树补全的线性时间算法。
Algorithms Mol Biol. 2020 Apr 13;15:6. doi: 10.1186/s13015-020-00166-1. eCollection 2020.
10
Forcing external constraints on tree inference using ASTRAL.使用 ASTRAL 强制对树推断施加外部约束。
BMC Genomics. 2020 Apr 16;21(Suppl 2):218. doi: 10.1186/s12864-020-6607-z.