A deep-learning method for detecting DNA methylation state from Oxford Nanopore sequencing reads
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v0.2.0
make –reference_path not a required input in extract and call_mods module
handle gz file in call_freq script
v0.1.10
make sure results of each read be written together in call_mods’ output
v0.1.9
enable multi-class (>=3) training/predicting,
fix bug of extrating contig name from fast5s
v0.1.8
modify denoise module fix success_file bug update README
v0.1.7
Prevent Queue.qsize() from raising NotImplementedError on Mac OS X (github: vterron/lemon@9ca6b4b) covert raw signals to pA values before normalization in extract_feature module add denoise module add module-chosen options of model (rnn/base/cnn), re-train human model
v0.1.6
add option –positions in extract_features module, add option/function of binary_format feature file to speed up training
v0.1.5
normalize probs before output
v0.1.4
change the loss function to weighted_cross_entropy_with_logits, allow training using unbalanced samples.
v0.1.3
fix the deadlock issue in multiprocessing
v0.1.2
add MANIFEST.in file
v0.1.1
3 modules (extract, call_mods, train) supported
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