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HLMethy

Relabeling candidate m6As with multiple instance learning.

The misvm package should be installed at first, which can be downloaded from https://github.com/garydoranjr/misvm.

m6A_model_training.py

Usage: python {0} positive_dataset negative_dataset method model_file scale_file score_file reserved_file

This script is used to train a bag level miSVM/MISVM model.

method : method of selection

    0 -- miSVM
    
    1 -- MISVM

A bag index file 'bag_index'will be created in current path.

A feature encoding file 'train_features.txt' will be created in current path.

A model file 'svc.pkl' will be created in current path.

A normalized file 'scale.pkl' will be created in current path.

A prediction score file 'score.txt' will be created in current path.

A reserved samples file 'reserved.txt' will be created in current path.

Example: python m6A_model_training.py ./traindata/train_pos_example.txt ./traindata/train_neg_example.txt 1 svc.pkl scale.pkl score.txt reserved_samples.txt

m6A_model_prediction.py

Usage: python {0} dataset model_file scale_file predict_res

This script will generate scores to relabel the candidate m6A sites.

Example: python m6A_model_prediction.py ./traindata/test_example.txt ./svc.pkl ./scale.pkl predict_res

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HLMethy: Machine learning-based model to identify the hidden labels of candidate m6A modifications

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