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toxify

deep learning approach to classify animal toxins

Installation

  1. Get the repository for toxify
git clone https://github.com/tijeco/toxify.git
  1. Change into toxify repository
cd toxify
  1. Create conda environment with dependencies needed to run toxify
conda env create -f requirements.yml
  1. Activate toxify conda environment
source activate toxify_env
  1. Install toxify to the toxify conda environment
python setup.py install
  1. Run toxify
toxify predict <input.fasta>
  1. view results in <input.fasta>_toxify_predictions/predictions_proteins.csv
  2. Deactivate toxify conda environment
source deactivate

Custom training dataset

If you wish to train a different model with your own training data, that can be accomplished with toxify using the train sub command.

There are a few variables that can be modified in terms of setting up the model.

  • -pos can be followed by a list of protein sequence fasta files that you wish to constitute the positive dataset

  • -neg can be followed by a list of protein sequence fasta files that you wish to constitute the negative dataset

  • -maxLen is the maximum length (integer) of protein seqeunce to be included in the training set

  • -units is the number (integer) of gated recurrent units to be used in the model

  • -epochs is the number (integer) of training epochs to run for the model

  • lr is the learning_rate (float, 0 < lr < 1)

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deep learning approach to classify animal toxins

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