Literature DB >> 32730595

Triplet-based similarity score for fully multilabeled trees with poly-occurring labels.

Simone Ciccolella1, Giulia Bernardini1, Luca Denti1, Paola Bonizzoni1, Marco Previtali1, Gianluca Della Vedova1.   

Abstract

MOTIVATION: The latest advances in cancer sequencing, and the availability of a wide range of methods to infer the evolutionary history of tumors, have made it important to evaluate, reconcile and cluster different tumor phylogenies. Recently, several notions of distance or similarities have been proposed in the literature, but none of them has emerged as the golden standard. Moreover, none of the known similarity measures is able to manage mutations occurring multiple times in the tree, a circumstance often occurring in real cases.
RESULTS: To overcome these limitations, in this article, we propose MP3, the first similarity measure for tumor phylogenies able to effectively manage cases where multiple mutations can occur at the same time and mutations can occur multiple times. Moreover, a comparison of MP3 with other measures shows that it is able to classify correctly similar and dissimilar trees, both on simulated and on real data.
AVAILABILITY AND IMPLEMENTATION: An open source implementation of MP3 is publicly available at https://github.com/AlgoLab/mp3treesim. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Year:  2021        PMID: 32730595     DOI: 10.1093/bioinformatics/btaa676

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  1 in total

1.  BiTSC 2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data.

Authors:  Ziwei Chen; Fuzhou Gong; Lin Wan; Liang Ma
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

  1 in total

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