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

被引：0
作者：
Magda Markowska
Tomasz Cąkała
BłaŻej Miasojedow
Bogac Aybey
Dilafruz Juraeva
Johanna Mazur
Edith Ross
Eike Staub
Ewa Szczurek
机构：
[1] University of Warsaw,
[2] Faculty of Mathematics,undefined
[3] Informatics and Mechanics,undefined
[4] Medical University of Warsaw,undefined
[5] Postgraduate School of Molecular Medicine,undefined
[6] Merck Healthcare KGaA,undefined
[7] Translational Medicine,undefined
[8] Oncology Bioinformatics,undefined
来源：
Genome Biology | / 23卷
关键词：
Copy number alterations; Tumor evolution; Single-cell sequencing; Probabilistic model; MCMC sampling;
D O I：
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学科分类号：
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.
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