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Dependencies:
This software requires the Python 3.0 or above to be install on your system. If you donot have Python in your system so please install the python by using this link https://www.python.org/downloads/. Then install the following dependencies by typing the command “pip install dependency_name” in the command prompt.
1. Pandas
2. Pickle
3. NumPy
4. Scikit-learn
5. CatBoost
After successful installation of all the dependencies, execute the “AlzGenPred.py” script using the below given command from any editor. The AlzGenPred.py and topological_features.csv can be downloaded by clicking on the respective name in the given command.
$ python AlzGenPred.py --file topological_features.csv
If you are not aware about the feature generation (topological_features.csv) then please use this well documented tutorial.
Input File:
User must give the input network features generated from the defined procedure to the script. The user can use this topological_features.csv and a well documented tutorial for input preparation. Please prepare the input as like given file otherwise the tool will give the error.
Output File: User will get the prediction result in an output file
"Output_AD_classification.csv" consisting of Gene name, prediction and prediction probability score in the AlzGenPred folder.
Output file format
If you are getting the CatBoost model version error so please download this script and generate the model using the Final_input_features.csv in your computer to avoid such error.
Feel free to write at shuklarohit815@gmail.com for any assistance.
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