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Example Modelling with cudaMMC

Follow these steps to successfully run the example modeling using cudaMMC:

  1. Set Paths in Config File

Firstly, you need to ensure the paths in the configuration file are correctly set. You can do this by running:

python set_paths_in_config.py -d /absolute/path/to/the/example_data -c /absolute/path/to/the/example_data/stg_gpu_example_config.ini

Note: This script will modify the stg_gpu_example_config.ini file. It is advised to keep a backup of the original configuration file.

  1. Run Modelling using cudaMMC

With the paths correctly set, you can now initiate the modeling using cudaMMC:

cudaMMC -s /path/to/the/example_data/stg_gpu_example_config.ini -c chr14:35138000-36160000 -o ./sim_out/

This will model the segment from chr14:35138000-36160000 and store the output in the ./sim_out/ directory.

  1. Convert Output to mmCIF Format

The native output from cudaMMC is in the .hcm format. For visualization purposes, it is beneficial to convert this into the .mmCIF format which can then be viewed using software like UCFC Chimera.

Prerequisites:

  • Ensure you have the numpy package installed. If not, you can install it using pip:

pip install numpy

To perform the conversion, run: python convert_hcm2cif.py -i /sim_out/ -s 5000 -c /path/to/cudaMMC

You can now use UCFC Chimera to visualize the .mmCIF files generated.

We hope this guide assists you in running the example modeling smoothly. If you face any issues, please refer to the documentation or contact support.