Linear-time algorithms for phylogenetic tree completion under Robinson-Foulds distance.

IF 1.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Algorithms for Molecular Biology Pub Date : 2020-04-13 eCollection Date: 2020-01-01 DOI:10.1186/s13015-020-00166-1
Mukul S Bansal
{"title":"Linear-time algorithms for phylogenetic tree completion under Robinson-Foulds distance.","authors":"Mukul S Bansal","doi":"10.1186/s13015-020-00166-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>We consider two fundamental computational problems that arise when comparing phylogenetic trees, rooted or unrooted, with non-identical leaf sets. The first problem arises when comparing two trees where the leaf set of one tree is a proper subset of the other. The second problem arises when the two trees to be compared have only partially overlapping leaf sets. The traditional approach to handling these problems is to first restrict the two trees to their common leaf set. An alternative approach that has shown promise is to first <i>complete</i> the trees by adding missing leaves, so that the resulting trees have identical leaf sets. This requires the computation of an optimal completion that minimizes the distance between the two resulting trees over all possible completions.</p><p><strong>Results: </strong>We provide optimal linear-time algorithms for both completion problems under the widely-used Robinson-Foulds (RF) distance measure. Our algorithm for the first problem improves the time complexity of the current fastest algorithm from quadratic (in the size of the two trees) to linear. No algorithms have yet been proposed for the more general second problem where both trees have missing leaves. We advance the study of this general problem by proposing a useful restricted version of the general problem and providing optimal linear-time algorithms for the restricted version. Our experimental results on biological data sets suggest that completion-based RF distances can be very different compared to traditional RF distances.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"6"},"PeriodicalIF":1.5000,"publicationDate":"2020-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-00166-1","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithms for Molecular Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13015-020-00166-1","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 3

Abstract

Background: We consider two fundamental computational problems that arise when comparing phylogenetic trees, rooted or unrooted, with non-identical leaf sets. The first problem arises when comparing two trees where the leaf set of one tree is a proper subset of the other. The second problem arises when the two trees to be compared have only partially overlapping leaf sets. The traditional approach to handling these problems is to first restrict the two trees to their common leaf set. An alternative approach that has shown promise is to first complete the trees by adding missing leaves, so that the resulting trees have identical leaf sets. This requires the computation of an optimal completion that minimizes the distance between the two resulting trees over all possible completions.

Results: We provide optimal linear-time algorithms for both completion problems under the widely-used Robinson-Foulds (RF) distance measure. Our algorithm for the first problem improves the time complexity of the current fastest algorithm from quadratic (in the size of the two trees) to linear. No algorithms have yet been proposed for the more general second problem where both trees have missing leaves. We advance the study of this general problem by proposing a useful restricted version of the general problem and providing optimal linear-time algorithms for the restricted version. Our experimental results on biological data sets suggest that completion-based RF distances can be very different compared to traditional RF distances.

Abstract Image

Abstract Image

Abstract Image

Robinson-Foulds距离下系统发育树补全的线性时间算法。
背景:我们考虑两个基本的计算问题,出现在比较系统发育树,有根或无根,与不相同的叶集。第一个问题出现在比较两棵树时,其中一棵树的叶集是另一棵树的适当子集。当要比较的两棵树只有部分重叠的叶集时,第二个问题就出现了。处理这些问题的传统方法是首先将两棵树限制在它们的公共叶集中。另一种有希望的方法是首先通过添加缺失的叶子来完成树,这样得到的树就有相同的叶子集。这就要求在所有可能的完井中,计算出一种最优完井方法,使两个结果树之间的距离最小。结果:在广泛使用的Robinson-Foulds (RF)距离测量下,我们为这两个完井问题提供了最优的线性时间算法。我们对第一个问题的算法将目前最快的算法的时间复杂度从二次(两棵树的大小)提高到线性。对于更普遍的第二个问题,即两棵树都缺叶的问题,还没有提出算法。我们提出了一个有用的一般问题的限制版本,并提供了限制版本的最优线性时间算法,从而推进了这一一般问题的研究。我们在生物数据集上的实验结果表明,与传统的射频距离相比,基于完井的射频距离可能有很大不同。
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
Algorithms for Molecular Biology
Algorithms for Molecular Biology 生物-生化研究方法
CiteScore
2.40
自引率
10.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Algorithms for Molecular Biology publishes articles on novel algorithms for biological sequence and structure analysis, phylogeny reconstruction, and combinatorial algorithms and machine learning. Areas of interest include but are not limited to: algorithms for RNA and protein structure analysis, gene prediction and genome analysis, comparative sequence analysis and alignment, phylogeny, gene expression, machine learning, and combinatorial algorithms. Where appropriate, manuscripts should describe applications to real-world data. However, pure algorithm papers are also welcome if future applications to biological data are to be expected, or if they address complexity or approximation issues of novel computational problems in molecular biology. Articles about novel software tools will be considered for publication if they contain some algorithmically interesting aspects.
×
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