modules/
mobster

mobster is a package that implements a model-based approach for subclonal deconvolution of cancer genome sequencing data.

The package integrates evolutionary theory (i.e., population) and Machine-Learning to analyze (e.g., whole-genome) bulk data from cancer samples. This analysis relates to clustering; we approach it via a maximum-likelihood formulation of Dirichlet mixture models, and use bootstrap routines to assess the confidence of the parameters.