Work

Reconstruction of clonal trees and tumor composition from multi-sample sequencing data

Year: 2015

Type: article

Abstract: MOTIVATION: 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. RESULTS: 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. AVAILABILITY AND IMPLEMENTATION: An implementation of AncesTree is available at: http://compbio.cs.brown.edu/software.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btv261

Authors: Mohammed El-Kebir, Layla Oesper, Hannah Acheson-Field, Benjamin J. Raphael

Institution: Brown University

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,989

Funders: National Human Genome Research Institute, National Cancer Institute