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 are 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. We model the evolution of a tumor by segmental deletions and amplifications, and gauge distance from profile a to b by the minimum number of events needed to transform a into b. 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. 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. We assess the efficiency and quality of our algorithms on simulated instances.

El Kebir, M., Raphael, B., Shamir, R., Sharan, R., Zaccaria, S., Zehavi, M., et al. (2016). Copy-number evolution problems: Complexity and algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.137-149). Springer Verlag [10.1007/978-3-319-43681-4_11].

Copy-number evolution problems: Complexity and algorithms

ZACCARIA, SIMONE;
2016

Abstract

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 are 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. We model the evolution of a tumor by segmental deletions and amplifications, and gauge distance from profile a to b by the minimum number of events needed to transform a into b. 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. 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. We assess the efficiency and quality of our algorithms on simulated instances.
Si
paper
Theoretical Computer Science; Computer Science (all)
English
International Workshop on Algorithms in Bioinformatics, WABI 2016 - August 22-24
9783319436807
http://springerlink.com/content/0302-9743/copyright/2005/
El Kebir, M., Raphael, B., Shamir, R., Sharan, R., Zaccaria, S., Zehavi, M., et al. (2016). Copy-number evolution problems: Complexity and algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.137-149). Springer Verlag [10.1007/978-3-319-43681-4_11].
El Kebir, M; Raphael, B; Shamir, R; Sharan, R; Zaccaria, S; Zehavi, M; Zeira, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/132160
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