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CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples

Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, an...

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Detalles Bibliográficos
Autores principales: Lu, Bingxin, Curtius, Kit, Graham, Trevor A., Yang, Ziheng, Barnes, Chris P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283241/
https://www.ncbi.nlm.nih.gov/pubmed/37340508
http://dx.doi.org/10.1186/s13059-023-02983-0
Descripción
Sumario:Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, and mutation rates from total copy numbers of longitudinal samples. Our extensive simulations suggest CNETML performs well on copy numbers relative to ploidy and under slight violation of model assumptions. The application of CNETML to real data generates results consistent with previous discoveries and provides novel early copy number events for further investigation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02983-0.