von Heydebreck Anja, Gunawan Bastian, Füzesi László
Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany.
Biostatistics. 2004 Oct;5(4):545-56. doi: 10.1093/biostatistics/kxh007.
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.
我们提出了一种用于模拟人类肿瘤基因变化之间依赖性的新方法。在实体瘤中，基因改变的数据通常仅在单个时间点可用，无法直接洞察基因事件的顺序。在我们的方法中，假定基因肿瘤的发展和进展遵循概率树模型。我们展示了如何使用最大似然估计来重建给定肿瘤类型中基因改变之间依赖性的树模型。我们通过将该方法应用于173例透明细胞肾细胞癌的细胞遗传学数据来说明该方法的使用，得出了该肿瘤核型进化的模型。
