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Artificial neural networks for non canonical base modification detection

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Druid

v0.1internal release, no tests

Druid is a fork of the hybrid neural net platform for training, evaluating and deploying neural network models that originally act as taxonomic classifiers of raw nanopore signal (Achilles). It reimplements the basecaller function of Chiron as a Keras model with the specific purpose to detect non canonical base modifications.

Install


pip install git+https://github.com/esteinig/druid  # does not install tensorflow-gpu or keras

PoreMongo dependency, which can for now be installed with:

pip install git+https://github.com/esteinig/poremongo

Documentation


Coming soon.

druid.readthedocs.io

Contributors


  • Eike Steinig
  • Lachlan Coin

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Artificial neural networks for non canonical base modification detection

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