Python implementation of MeDeCom's cppTAfact.
The tool has been tested on python 3.9.13, but earlier versions should work just fine. pyMeDeCom and its dependencies can be installed as follows:
git clone [email protected]:CompEpigen/pyMeDeCom.git
cd pyMeDeCom
pip install .
An example on how to run pyMeDeCom can be found in tests/runMeDeCom.py.
The run_parallel function starts the model fitting process.
kcorresponds to the number of latent components, ninit to the number of random initializations of the returned
T and A matrices as in MeDeCom, niter to the number of iterations per initialization and
ncores to the number of cores that are used to fit the model.