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El-Kebir, Mohammed; Oesper, Layla; Acheson-Field, Hannah; Raphael, Benjamin J
Bioinformatics, 06/2015, Letnik: 31, Številka: 12Journal Article
DNA sequencing of multiple samples from the same tumor provides data to analyze the process of clonal evolution in the population of cells that give rise to a tumor. We formalize the problem of reconstructing the clonal evolution of a tumor using single-nucleotide mutations as the variant allele frequency (VAF) factorization problem. We derive a combinatorial characterization of the solutions to this problem and show that the problem is NP-complete. We derive an integer linear programming solution to the VAF factorization problem in the case of error-free data and extend this solution to real data with a probabilistic model for errors. The resulting AncesTree algorithm is better able to identify ancestral relationships between individual mutations than existing approaches, particularly in ultra-deep sequencing data when high read counts for mutations yield high confidence VAFs. An implementation of AncesTree is available at: http://compbio.cs.brown.edu/software.
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