Clonality inference in multiple tumor samples using phylogeny
S Malikic, AW McPherson, N Donmez… - …, 2015 - academic.oup.com
Bioinformatics, 2015•academic.oup.com
Motivation: 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. Results: 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 …
during cancer progression. Although recent research suggests that this heterogeneity has
clinical implications, in silico determination of the clonal subpopulations remains a
challenge. Results: 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 …
Abstract
Motivation: 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.
Results: 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.
Availability and implementation: CITUP is freely available at: http://sourceforge.net/projects/citup/.
Contact: cenk@sfu.ca
Supplementary information: Supplementary data are available at Bioinformatics online.
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