Abstract
The last decade brought a significant increase in the amount of data and a variety of new inference methods for reconstructing the detailed evolutionary history of various cancers. This brings the need of designing efficient procedures for comparing rooted trees representing the evolution of mutations in tumor phylogenies. Bernardini et al. [CPM 2019] recently introduced a notion of the rearrangement distance for fullylabelled trees motivated by this necessity. This notion originates from two operations: one that permutes the labels of the nodes, the other that affects the topology of the tree. Each operation alone defines a distance that can be computed in polynomial time, while the actual rearrangement distance, that combines the two, was proven to be NPhard.
We answer two open question left unanswered by the previous work. First, what is the complexity of computing the permutation distance? Second, is there a constantfactor approximation algorithm for estimating the rearrangement distance between two arbitrary trees? We answer the first one by showing, via a twoway reduction, that calculating the permutation distance between two trees on n nodes is equivalent, up to polylogarithmic factors, to finding the largest cardinality matching in a sparse bipartite graph. In particular, by plugging in the algorithm of Liu and Sidford [ArXiv 2020], we obtain an ?̃(n^{4/3+o(1}) time algorithm for computing the permutation distance between two trees on n nodes. Then we answer the second question positively, and design a lineartime constantfactor approximation algorithm that does not need any assumption on the trees.
BibTeX  Entry
@InProceedings{bernardini_et_al:LIPIcs:2020:12131,
author = {Giulia Bernardini and Paola Bonizzoni and Paweł Gawrychowski},
title = {{On Two Measures of Distance Between FullyLabelled Trees}},
booktitle = {31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020)},
pages = {6:16:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {9783959771498},
ISSN = {18688969},
year = {2020},
volume = {161},
editor = {Inge Li G{\o}rtz and Oren Weimann},
publisher = {Schloss DagstuhlLeibnizZentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2020/12131},
URN = {urn:nbn:de:0030drops121318},
doi = {10.4230/LIPIcs.CPM.2020.6},
annote = {Keywords: Tree distance, Cancer progression, Approximation algorithms, Finegrained complexity}
}
Keywords: 

Tree distance, Cancer progression, Approximation algorithms, Finegrained complexity 
Collection: 

31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020) 
Issue Date: 

2020 
Date of publication: 

09.06.2020 