/SilencerEnhancerPredict

Primary LanguageJupyter Notebook

CNN model for predicting enhancers and silencers

How to use

Traing a model

input: data file, and target directory for the results

    A data file includes training and validation sample sets. 
    Each sample set is represented by:
       a one-hot-encode DNA sequence matrix in a size of N * 1000 * 4, 
       a 3-class matrix in a size of N * 3. N is the number of samples.

example: python train.py ./examples/data_training.hdf5 ./examples/

output: in the directory ./examples/

    auc.txt

    fpr_threshold_scores.txt
    
    model_weights.hdf5

Making predictions with a built model,

input: data file, model file,

example: python train.py ./examples/data_prediction.hdf5 ./examples/model_weights.hdf5

output: ./examples/data_prediction.hdf5.predict.data

Featuring

%pip install Bio

%pip install pybedtools

!python /content/SilencerEnhancerPredict/train.py /content/SilencerEnhancerPredict/examples/training_200seq_2class.hdf5 /content/SilencerEnhancerPredict/examples/

!python /content/SilencerEnhancerPredict/train.py /content/SilencerEnhancerPredict/examples/training_200seq_2class.hdf5 /content/SilencerEnhancerPredict/examples/model_weights.hdf5