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
相关论文
共 50 条
  • [41] Tumor Clonality Determinations Using Targeted Next-Generation Sequencing
    Geurts-Giele, W. R.
    Atmodimedjo, P.
    Dubbink, H. J.
    Dinjens, W. N.
    JOURNAL OF MOLECULAR DIAGNOSTICS, 2013, 15 (06): : 919 - 919
  • [42] Tumor burden and clonality in multiple intestinal neoplasia mouse/normal mouse aggregation chimeras
    Novelli, MR
    Wasan, H
    Rosewell, I
    Bee, J
    Tomlinson, IP
    Wright, NA
    Bodmer, WF
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1999, 96 (22) : 12553 - 12558
  • [43] Tumor clonality detection using next generation sequencing data.
    Dees, Nathan D.
    Miller, Christopher A.
    White, Brian S.
    Schierding, William
    Vij, Ravi
    Tomasson, Michael H.
    Welch, John S.
    Graubert, Timothy A.
    Walter, Matthew J.
    Ley, Timothy J.
    DiPersio, John F.
    Mardis, Elaine R.
    Wilson, Richard K.
    Ding, Li
    CANCER RESEARCH, 2013, 73 (08)
  • [44] FLEXIBLE PHYLOGENY RECONSTRUCTION - A REVIEW OF PHYLOGENETIC INFERENCE PACKAGES USING PARSIMONY
    SANDERSON, MJ
    HORTORIUM, LHB
    SYSTEMATIC ZOOLOGY, 1990, 39 (04): : 414 - 420
  • [45] Ancestry inference of 96 population samples using microhaplotypes
    Ozlem Bulbul
    Andrew J. Pakstis
    Usha Soundararajan
    Cemal Gurkan
    Jane E. Brissenden
    Janet M. Roscoe
    Baigalmaa Evsanaa
    Ariunaa Togtokh
    Peristera Paschou
    Elena L. Grigorenko
    David Gurwitz
    Sharon Wootton
    Robert Lagace
    Joseph Chang
    William C. Speed
    Kenneth K. Kidd
    International Journal of Legal Medicine, 2018, 132 : 703 - 711
  • [46] INFERENCE OF TREE-GRAMMARS USING NEGATIVE SAMPLES
    BARRERO, A
    PATTERN RECOGNITION, 1991, 24 (01) : 1 - 8
  • [47] Model based inference using ranked set samples
    Ozturk, Omer
    Kavlak, Konul Bayramoglu
    SURVEY METHODOLOGY, 2018, 44 (01) : 1 - 16
  • [48] Statistical inference for a ratio of dispersions using paired samples
    Bonett, DG
    Seier, E
    JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2003, 28 (01) : 21 - 30
  • [49] Weibull inference using trimmed samples and prior information
    Arturo J. Fernández
    Statistical Papers, 2009, 50 : 119 - 136
  • [50] Ancestry inference of 96 population samples using microhaplotypes
    Bulbul, Ozlem
    Pakstis, Andrew J.
    Soundararajan, Usha
    Gurkan, Cemal
    Brissenden, Jane E.
    Roscoe, Janet M.
    Evsanaa, Baigalmaa
    Togtokh, Ariunaa
    Paschou, Peristera
    Grigorenko, Elena L.
    Gurwitz, David
    Wootton, Sharon
    Lagace, Robert
    Chang, Joseph
    Speed, William C.
    Kidd, Kenneth K.
    INTERNATIONAL JOURNAL OF LEGAL MEDICINE, 2018, 132 (03) : 703 - 711