CONET: copy number event tree model of evolutionary tumor history for single-cell data

被引：15

作者：

Markowska, Magda ^{[1
,2
]}

Cakala, Tomasz ^{[1
]}

Miasojedow, Blazej ^{[1
]}

Aybey, Bogac ^{[3
]}

Juraeva, Dilafruz ^{[3
]}

Mazur, Johanna ^{[3
]}

Ross, Edith ^{[3
]}

Staub, Eike ^{[3
]}

Szczurek, Ewa ^{[1
]}

机构：

[1] Univ Warsaw, Fac Math Informat & Mech, Banacha 2, Warsaw, Poland

[2] Med Univ Warsaw, Postgrad Sch Mol Med, Ks Trojdena 2a St, Warsaw, Poland

[3] Merck Healthcare KGaA, Translat Med, Oncol Bioinformat, Frankfurter Str 250, D-64293 Darmstadt, Germany

来源：

GENOME BIOLOGY | 2022年 / 23卷 / 01期

关键词：

Copy number alterations; Tumor evolution; Single-cell sequencing; Probabilistic model; MCMC sampling; CIRCULAR BINARY SEGMENTATION; WHOLE-GENOME; CANCER; DNA; INFERENCE; PHYLOGENY; POPULATIONS;

D O I：

10.1186/s13059-022-02693-z

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Copy number alterations constitute important phenomena in tumor evolution. Whole genome single-cell sequencing gives insight into copy number profiles of individual cells, but is highly noisy. Here, we propose CONET, a probabilistic model for joint inference of the evolutionary tree on copy number events and copy number calling. CONET employs an efficient, regularized MCMC procedure to search the space of possible model structures and parameters. We introduce a range of model priors and penalties for efficient regularization. CONET reveals copy number evolution in two breast cancer samples, and outperforms other methods in tree reconstruction, breakpoint identification and copy number calling.

引用

页数：35

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