mhn: A Python Package for Analyzing Cancer Progression with Mutual Hazard Networks

Mutual Hazard Networks (MHN) were first introduced by Schill et al. (2019) and are used to model cancer progression. This Python package provides tools to work with MHNs. It includes optimizer classes that enable training an MHN with just a few lines of code. Additionally, it offers utility functions such as plotting MHNs and generating artificial tumor histories for a given MHN. The package also incorporates state space restriction, allowing the training of MHNs with well over 100 events, provided that individual samples contain no more than about 25 active events.

Contents:

• Installation
  • Install the mhn package using pip
  • Use the CUDA implementation to accelerate computations
• How to train your MHN
  • Configure the Optimizer
  • Train a new MHN model
• A detailed description of mhn’s subpackages, submodules and functions
  • Directly callable functions and constants
  • The full_state_space subpackage
  • The training subpackage
  • The optimizers submodule
  • The model submodule
  • The utilities submodule
  • The mcmc subpackage

Indices and tables

• Index

• Module Index

• Search Page