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Genome Biol ; 23(1): 128, 2022 06 09.
Article in English | MEDLINE | ID: mdl-35681161

ABSTRACT

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.


Subject(s)
DNA Copy Number Variations , Neoplasms , Humans , Neoplasms/genetics , Neoplasms/pathology
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