All data used in this study is available in the data folder on this repository. The file named 240_B.txt is used for the major analysis of this study while the journal_data.csv file is used for creating a supplementary table.
All code used to generate the figures in this study and all relevant statistics are available in the notebooks folder in the Figure.ipynb notebook file.
In order to run the notebook, we reccomend first either creating a conda environment using the environment.yml file we provide in our dependencies folder. You can create the environment by running the following commands:
conda env create -f environment.yml
Once created, then just use the following command to activate your environement.
conda activate code_availability_env
If you are running the notebook in VSCode, then use the change kernel button to select the code_availability_env as the environment to run the notebook in. If you are running the notebook in Jupyter Notebook, then just make sure the environment is activated before running calling jupyter notebook to run the notebook.
If you do not want to use conda and have some other preference for environments or rather just don't use environments, you can use the requirements.txt file which will allow you to install all of the dependencies as well via pip:
pip install -r requirements.txt
Once this is done running, the notebook should run
We will be adding a google collab notebook that everyone can use to rerun the code to generate the figures as well in the near future.
###Citation Nitesh Kumar Sharma, Ram Ayyala, Dhrithi Deshpande, Yesha M Patel, Viorel Munteanu, Dumitru Ciorba, Andrada Fiscutean, Mohammad Vahed, Aditya Sarkar, Ruiwei Guo, Andrew Moore, Nicholas Darci-Maher, Nicole A Nogoy, Malak S. Abedalthagafi, Serghei Mangul bioRxiv 2023.07.31.551384; doi: https://doi.org/10.1101/2023.07.31.551384