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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Abstract

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:	12 Dec 2024 01:42
URI:	http://eprints.lse.ac.uk/id/eprint/100274

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