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