Date of this Version
Nucleic Acids Research
The progression and clonal development of tumors often involve amplifications and deletions of genomic DNA. Estimation of allele-specific copy number, which quantifies the number of copies of each allele at each variant loci rather than the total number of chromosome copies, is an important step in the characterization of tumor genomes and the inference of their clonal history. We describe a new method, Falcon, for finding somatic allele-specific copy number changes by next generation sequencing of tumors with matched normals. Falcon is based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, Falcon more effectively pools evidence from sites with low coverage. A modified Bayesian information criterion is used to guide model selection for determining the number of copy number events. Falcon is evaluated on in silico spike-in data and applied to the analysis of a pre-malignant colon tumor sample and late-stage colorectal adenocarcinoma from the same individual. The allele-specific copy number estimates obtained by Falcon allows us to draw detailed conclusions regarding the clonal history of the individual's colon cancer.
© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
adenocarcinoma, alleles, clonal evolution, colorectal neoplasms, gene dosage, high-throughput nucleotide sequencing, humans, neoplasms, sequence analysis, DNA, software
Chen, H., Bell, J. M., Zavala, N. A., Ji, H. P., & Zhang, N. R. (2015). Allele-Specific Copy Number Profiling by Next-Generation DNA Sequencing. Nucleic Acids Research, 43 (4), http://dx.doi.org/10.1093/nar/gku1252
Date Posted: 25 October 2018
This document has been peer reviewed.