deepbiome Documentation

Contents:

• Introduction
  • DeepBiome: a phylogenetic tree regularized deep neural network for microbiome data analysis
  • Microbiome data structure
  • DeepBiome
  • Selection of disease associated microbiome taxa
• Getting start with the classification problem.
• Getting start with the regression problem.
• Installation
  • Stable release
  • From sources
• Prerequisites
  • Data preprocessing
  • Configuration
• Usage
  • Preparing the dataset
  • Preparing the configufation
  • Training
  • Testing
  • Prediction
  • Cheatsheet for running the project on console
  • Summary
• Example : k fold cross-validation with an input file
  • 1. Load library
  • 2. Prepare the dataset
  • 3. Prepare the configuration
  • 4. Deepbiome Training
  • 5. Load the pre-trained network for training
  • 6. Load the pre-trained network for testing
  • 7. Load the pre-trained network for prediction
  • 8. Load trained weight matrix
  • 9. Taxa selection performance
  • 10. Draw phylogenetic tree
  • 11. Using covariates
• Example : k times repetition with the list of k input files
  • 1. Load library
  • 2. Prepare the dataset
  • 3. Prepare the configuration
  • 4. DeepBiome Training
  • 5. Load the pre-trained network for training
  • 6. Load the pre-trained network for testing
  • 7. Load the pre-trained network for prediction
  • 8. Load trained weight matrix
  • 9. Taxa selection performance
• Release History
  • Initial Release (YYYY-MM-DD)
• Minimum Version of Python and NumPy
• Credits
  • Maintainer
  • Contributors
• Contributing
  • Types of Contributions
  • Get Started!
  • Pull Request Guidelines