PHi-C2 is a Python package supported by mathematical and biophysical polymer modeling, that converts an input Hi-C matrix data into the polymer model's dynamics, structural conformations, and rheological features. PHi-C2 as the phic package (maintaind on GitHub) is freely available and can be installed from the Python package index. The updated optimization algorithm to regenerate a highly similar Hi-C matrix provides a fast and accurate optimal solution compared to the previous version by eliminating a computational bottleneck in the iterative optimization process. In addition, without introducing a Python environment in the user's local platform, PHi-C2 runs on Google Colab. Users can easily change parameters and check the results in the notebook. Additionally, we shipped a command-line interface for convenient application.

PHi-C (Polymer dynamics deciphered from Hi-C data)

PHi-C consists of Python3 codes available at GitHub for deciphering Hi-C data into polymer dynamics simulations. The input is a contact matrix data generated from a hic file through Juicer. PHi-C assumes that a genomic region of interest at an appropriate resolution can be modeled using a polymer network model, including attractive and repulsive interactions between monomers. Instead of finding optimized 3D conformations, PHi-C's optimization procedure provides optimal interaction parameters of the polymer network model. We can then reconstruct an optimized contact matrix. Finally, we can carry out polymer dynamics simulations of the polymer network model equipped with the optimal interaction parameters.