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MIPUP: minimum perfect unmixed phylogenies for multi-sampled tumors via branchings and ILP

Husić, Edin, Li, Xinyue, Hujdurović, Ademir, Mehine, Miika, Rizzi, Romeo, Mäkinen, Veli, Milanič, Martin and Tomescu, Alexandru I. (2019) MIPUP: minimum perfect unmixed phylogenies for multi-sampled tumors via branchings and ILP. Bioinformatics, 35 (5). pp. 769-777. ISSN 1367-4803

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Identification Number: 10.1093/bioinformatics/bty683


Motivation: Discovering the evolution of a tumor may help identify driver mutations and provide a more comprehensive view on the history of the tumor. Recent studies have tackled this problem using multiple samples sequenced from a tumor, and due to clinical implications, this has attracted great interest. However, such samples usually mix several distinct tumor subclones, which confounds the discovery of the tumor phylogeny. Results: We study a natural problem formulation requiring to decompose the tumor samples into several subclones with the objective of forming a minimum perfect phylogeny. We propose an Integer Linear Programming formulation for it, and implement it into a method called MIPUP. We tested the ability of MIPUP and of four popular tools LICHeE, AncesTree, CITUP, Treeomics to reconstruct the tumor phylogeny. On simulated data, MIPUP shows up to a 34% improvement under the ancestor-descendant relations metric. On four real datasets, MIPUP's reconstructions proved to be generally more faithful than those of LICHeE.

Item Type: Article
Additional Information: © 2018 The Authors
Divisions: Mathematics
Subjects: Q Science > Q Science (General)
Date Deposited: 26 Mar 2019 12:24
Last Modified: 20 Oct 2021 00:04

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