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Complexity and algorithms for copy-number evolution problems

BACKGROUND: Cancer is an evolutionary process characterized by the accumulation of somatic mutations in a population of cells that form a tumor. One frequent type of mutations is copy number aberrations, which alter the number of copies of genomic regions. The number of copies of each position along...

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Autores principales: El-Kebir, Mohammed, Raphael, Benjamin J., Shamir, Ron, Sharan, Roded, Zaccaria, Simone, Zehavi, Meirav, Zeira, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5433102/
https://www.ncbi.nlm.nih.gov/pubmed/28515774
http://dx.doi.org/10.1186/s13015-017-0103-2
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author El-Kebir, Mohammed
Raphael, Benjamin J.
Shamir, Ron
Sharan, Roded
Zaccaria, Simone
Zehavi, Meirav
Zeira, Ron
author_facet El-Kebir, Mohammed
Raphael, Benjamin J.
Shamir, Ron
Sharan, Roded
Zaccaria, Simone
Zehavi, Meirav
Zeira, Ron
author_sort El-Kebir, Mohammed
collection PubMed
description BACKGROUND: Cancer is an evolutionary process characterized by the accumulation of somatic mutations in a population of cells that form a tumor. One frequent type of mutations is copy number aberrations, which alter the number of copies of genomic regions. The number of copies of each position along a chromosome constitutes the chromosome’s copy-number profile. Understanding how such profiles evolve in cancer can assist in both diagnosis and prognosis. RESULTS: We model the evolution of a tumor by segmental deletions and amplifications, and gauge distance from profile [Formula: see text] to [Formula: see text] by the minimum number of events needed to transform [Formula: see text] into [Formula: see text] . Given two profiles, our first problem aims to find a parental profile that minimizes the sum of distances to its children. Given k profiles, the second, more general problem, seeks a phylogenetic tree, whose k leaves are labeled by the k given profiles and whose internal vertices are labeled by ancestral profiles such that the sum of edge distances is minimum. CONCLUSIONS: For the former problem we give a pseudo-polynomial dynamic programming algorithm that is linear in the profile length, and an integer linear program formulation. For the latter problem we show it is NP-hard and give an integer linear program formulation that scales to practical problem instance sizes. We assess the efficiency and quality of our algorithms on simulated instances. AVAILABILITY: https://github.com/raphael-group/CNT-ILP ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13015-017-0103-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-54331022017-05-17 Complexity and algorithms for copy-number evolution problems El-Kebir, Mohammed Raphael, Benjamin J. Shamir, Ron Sharan, Roded Zaccaria, Simone Zehavi, Meirav Zeira, Ron Algorithms Mol Biol Research BACKGROUND: Cancer is an evolutionary process characterized by the accumulation of somatic mutations in a population of cells that form a tumor. One frequent type of mutations is copy number aberrations, which alter the number of copies of genomic regions. The number of copies of each position along a chromosome constitutes the chromosome’s copy-number profile. Understanding how such profiles evolve in cancer can assist in both diagnosis and prognosis. RESULTS: We model the evolution of a tumor by segmental deletions and amplifications, and gauge distance from profile [Formula: see text] to [Formula: see text] by the minimum number of events needed to transform [Formula: see text] into [Formula: see text] . Given two profiles, our first problem aims to find a parental profile that minimizes the sum of distances to its children. Given k profiles, the second, more general problem, seeks a phylogenetic tree, whose k leaves are labeled by the k given profiles and whose internal vertices are labeled by ancestral profiles such that the sum of edge distances is minimum. CONCLUSIONS: For the former problem we give a pseudo-polynomial dynamic programming algorithm that is linear in the profile length, and an integer linear program formulation. For the latter problem we show it is NP-hard and give an integer linear program formulation that scales to practical problem instance sizes. We assess the efficiency and quality of our algorithms on simulated instances. AVAILABILITY: https://github.com/raphael-group/CNT-ILP ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13015-017-0103-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-16 /pmc/articles/PMC5433102/ /pubmed/28515774 http://dx.doi.org/10.1186/s13015-017-0103-2 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
El-Kebir, Mohammed
Raphael, Benjamin J.
Shamir, Ron
Sharan, Roded
Zaccaria, Simone
Zehavi, Meirav
Zeira, Ron
Complexity and algorithms for copy-number evolution problems
title Complexity and algorithms for copy-number evolution problems
title_full Complexity and algorithms for copy-number evolution problems
title_fullStr Complexity and algorithms for copy-number evolution problems
title_full_unstemmed Complexity and algorithms for copy-number evolution problems
title_short Complexity and algorithms for copy-number evolution problems
title_sort complexity and algorithms for copy-number evolution problems
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5433102/
https://www.ncbi.nlm.nih.gov/pubmed/28515774
http://dx.doi.org/10.1186/s13015-017-0103-2
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