Clonality inference in multiple tumor samples using phylogeny

Intra-tumor heterogeneity presents itself through the evolution of subclones during cancer progression. Although recent research suggests that this heterogeneity has clinical implications, in silico determination of the clonal subpopulations remains a challenge. We address this problem through a nov...

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Bibliographic Details
Published in:Bioinformatics 2015-05, Vol.31 (9), p.1349-1356
Main Authors: Malikic, Salem, McPherson, Andrew W, Donmez, Nilgun, Sahinalp, Cenk S
Format: Article
Language:English
Subjects:
Algorithms
Bioinformatics
Cancer
Clonal Evolution
Combinatorial analysis
Contact
DNA Mutational Analysis
Evolution
Heterogeneity
High-Throughput Nucleotide Sequencing
Humans
Inference
Leukemia, Lymphocytic, Chronic, B-Cell - genetics
Leukemia, Myeloid, Acute - genetics
Mutation
Neoplasms - genetics
Phylogeny
Tumors
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Summary:Intra-tumor heterogeneity presents itself through the evolution of subclones during cancer progression. Although recent research suggests that this heterogeneity has clinical implications, in silico determination of the clonal subpopulations remains a challenge. We address this problem through a novel combinatorial method, named clonality inference in tumors using phylogeny (CITUP), that infers clonal populations and their frequencies while satisfying phylogenetic constraints and is able to exploit data from multiple samples. Using simulated datasets and deep sequencing data from two cancer studies, we show that CITUP predicts clonal frequencies and the underlying phylogeny with high accuracy. CITUP is freely available at: http://sourceforge.net/projects/citup/. cenk@sfu.ca Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btv003