NanoTensor

We propose a series of scripts, which are still in development, to label and train a multilayer Bidirectional long short-term memory recurrent neural network to base-call ONT-nanopore reads with modified bases.

INSTALLATION

Install BWA and make sure executable is in the PATH:

• git clone https://github.com/lh3/bwa.git
• cd bwa
• make
• export PATH=$PATH:$PWD

The easiest way to deal with the dependencies is to download Anaconda

• Download and Install Anaconda https://docs.continuum.io/anaconda/install
• git clone --recursive https://github.com/BD2KGenomics/nanopore-RNN
• cd nanopore-RNN
• conda env create --file requirements.yml
• source activate nanotensor
• make
• C executables created by signalAlign need to be in the PATH
• export PATH=$PATH:$PWD/signalAlign/bin
• Test installation
• make test

USAGE

TODO

Training using Nanonet

If you want to use Nanonet to train a network, you can use the script located here to embed aligned kmers into the fast5 file which can then be used with Nanonet.

Contributions

If you decide to help contribute please use pylint so our code is consistent. https://www.pylint.org/