https://arxiv.org/abs/1608.03644

https://github.com/QData/DeepMotif/blob/master/psb_talk_slides.pdf

@article{lanchantin2016deep,
  title={Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks},
  author={Lanchantin, Jack and Singh, Ritambhara and Wang, Beilun and Qi, Yanjun},
  journal={arXiv preprint arXiv:1608.03644},
  year={2016}
}

The main modeling code is written in Lua using torch Installation instructions are located here

After installing torch, install / update these packages by running the following:

luarocks install torch
luarocks install nn
luarocks install optim

To enable GPU acceleration with CUDA, you'll need to install CUDA 6.5 or higher as well as cutorch and cunn. You can install / update the torch CUDA libraries by running:

luarocks install cutorch
luarocks install cunn

Install git large file storage (LFS) in order to download the dataset directly from this git repository.

https://git-lfs.github.com/

Weblogo: http://weblogo.berkeley.edu/

R: https://www.r-project.org/

tar xvzf data/deepbind.tar.gz -C data/

You can train one of the 3 types of models (CNN, RNN, or CNN-RNN). Check the flags in main.lua for parameters to run the code.

For CNN model:

th main.lua -cnn

For CNN model:

th main.lua -rnn

For CNN-RNN model:

th main.lua -cnn -rnn

Once you have trained models, you can visualize the predictions.

Saliency Map

th saliency_map.lua

Temporal Output Values

th temporal_output_values.lua

Class Optimization

th class_optimization.lua