CRISPR-Deep-Learning

Repository for the CRISPR Deep Learning review article. It includes all the data and code to reproduce our analysis.

Requirements

The scripts are written in Python 3.7.4 (Anaconda version: 4.8.5) and run on Windows OS:

   Windows-10: 10.0.18362-SP0

• The versions of Python packages which we used are, specifically:

  Scikit-learn version: 0.21.3
  Numpy version: 1.16.5
  Pandas version: 0.25.1
  Scipy version: 1.3.1
  XGB version: 0.90
  Joblib version: 0.13.2

Content

• ./Data: the original and processed datasets that have been used in our analysis.
• ./Saved models: all the trained and re-trained models that we implemented in our study.
• ./Scripts: custom Python scripts to reproduce our results.

Citation

Vasileios Konstantakos, Anastasios Nentidis, Anastasia Krithara, Georgios Paliouras, CRISPR-Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning, Nucleic Acids Research, https://doi.org/10.1093/nar/gkac192

Support

You can submit bug reports using the GitHub issue tracker. If you have any other questions, please contact us at [email protected]