Clonality inference in multiple tumor samples using phylogeny

被引:134
|
作者
Malikic, Salem [1 ]
McPherson, Andrew W. [2 ]
Donmez, Nilgun [3 ]
Sahinalp, Cenk S. [1 ,4 ]
机构
[1] Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada
[2] BC Canc Agcy, Vancouver, BC, Canada
[3] Vancouver Prostate Ctr, Vancouver, BC, Canada
[4] Indiana Univ, Sch Informat & Comp, Bloomington, IN USA
基金
加拿大自然科学与工程研究理事会;
关键词
HETEROGENEITY; EVOLUTION; PROGRESSION;
D O I
10.1093/bioinformatics/btv003
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1349 / 1356
页数:8
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