CRISPRedict is an interpretable gRNA efficiency prediction model for CRISPR-Cas9 gene editing.
The scripts are written in Python 3.7.12 (Anaconda version: 4.8.5) and run on Windows OS:
Windows-10: 10.0.19041-SP0
- The versions of Python packages which we used are, specifically:
Scikit-learn version: 1.0.1
Statsmodels version: 0.10.2
Scikit-learn Genetic version: 0.4.1
Numpy version: 1.19.5
Pandas version: 1.1.5
Scipy version: 1.4.1
XGB version: 0.90
Matplotlib version: 3.2.2
Seaborn version: 0.11.2
Pingouin version: 0.3.12
Notebook version: 6.4.5
Xlrd version: 1.2.0
- ./Data: the original and processed datasets that have been used in our analysis.
- ./Notebooks: Jupyter notebooks that can be used to reproduce our results and demonstrate their usage.
- ./Saved models: all the trained and re-trained models that we implemented in our study.
- ./Scripts: custom Python scripts to reproduce our analysis.
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Vasileios Konstantakos, Anastasios Nentidis, Anastasia Krithara, Georgios Paliouras, CRISPRedict: The case for simple and interpretable efficiency prediction for CRISPR-Cas9 gene editing, bioRxiv 2022.04.07.486362; https://doi.org/10.1101/2022.04.07.486362
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Vasileios Konstantakos, Anastasios Nentidis, Anastasia Krithara, Georgios Paliouras, CRISPRedict: a CRISPR-Cas9 web tool for interpretable efficiency predictions, Nucleic Acids Research, 2022; https://doi.org/10.1093/nar/gkac466
You can submit bug reports using the GitHub issue tracker. If you have any other questions, please contact us at vkonstantakos@iit.demokritos.gr