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Maximum likelihood estimation of oncogenetic tree models

MPG-Autoren

von Heydebreck,  Anja
Max Planck Society;

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Zitation

von Heydebreck, A., Gunawan, B., & Füzesi, L. (2004). Maximum likelihood estimation of oncogenetic tree models. Biostatistics, 5(4), 545-556. doi:10.1093/biostatistics/kxh007.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-887C-C
Zusammenfassung
We present a new approach for modelling the dependences between genetic changes in human tumours. In solid tumours, data on genetic alterations are usually only available at a single point in time, allowing no direct insight into the sequential order of genetic events. In our approach, genetic tumour development and progression is assumed to follow a probabilistic tree model. We show how maximum likelihood estimation can be used to reconstruct a tree model for the dependences between genetic alterations in a given tumour type. We illustrate the use of the proposed method by applying it to cytogenetic data from 173 cases of clear cell renal cell carcinoma, arriving at a model for the karyotypic evolution of this tumour.