RESCVE

This is the repo for our manuscript "Representation of missense variants for predicting modes of action"

Environment

We recommend using a conda environment to run the code. The environment can be created using the following command:

conda env create -f RESCVE.yml

then activate the environment using:

conda activate RESCVE

Data

Please download AlphaFold predicted structures to data/Protein/ directory and change the files in data/Protein/uniprot.ID/ to your path.

The other data except HGMD data that we used in training process are provided under the data/ folder.

For MSA, we provided the files here: https://drive.google.com/file/d/1iu32tVQZ_N9WYJ0a8Xeh25uLACZVsBI7/view?usp=sharing. Please download the file and extract it to data/MSA/

Run

To run the code, please use the following command:

python RESCVE.py --mode Required --device Optional --seed Optional

Please check the comments in the file RESCVE.py for more details about which mode to use.