Genome Biology, 2023-06, Vol.24 (1), p.144-144, Article 144
2023
Details
- Autor(en) / Beteiligte
- Titel
- CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples
- Ist Teil von
- Genome Biology, 2023-06, Vol.24 (1), p.144-144, Article 144
- Ort / Verlag
- England: BioMed Central
- Erscheinungsjahr
- 2023
- Link zum Volltext
- Quelle
- SpringerLink Journals
- Beschreibungen/Notizen
- 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.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1474-760X, 1474-7596eISSN: 1474-760XDOI: 10.1186/s13059-023-02983-0Titel-ID: cdi_doaj_primary_oai_doaj_org_article_5e78e58832ea49fca3b1f1cb351c076f
- Format
- –
- Schlagworte
- Cancer, Cell cycle, Chromosomes, Cloning, Copy number, Copy number alteration, DNA Copy Number Variations, Evolution, Genetic testing, Genomes, Humans, Low-coverage sequencing, Markov analysis, Maximum likelihood, Method, Model of evolution, Mutation, Mutation Rate, Mutation rates, Neoplasms, Phylogeny, Phylogeny inference, Ploidy