url: https://genomenet.github.io/deepG
development:
  mode: release
  version_label: default
template:
  bootstrap: 5
  bootswatch: spacelab
navbar:
  structure:
    left:
    - reference
    - notebooks
    - tutorials
    right: github
  components:
    home: ~
    reference:
      icon: fa fa-file-alt
      text: Reference
      href: reference/index.html
    notebooks:
      text: Notebooks
      menu:
      - text: "deepG tutorial"
        href: https://colab.research.google.com/drive/175jIdXcDcgPUvaBo2rH2Lupbpjnp5O7G?usp=sharing
      - text: "Read-length level: Human contamination"
        href: https://colab.research.google.com/drive/1Eolc0koMNM1zkuO4XyVM58ImeF1BpRiH?usp=sharing
      - text: "Locus level: CRISPR detection"
        href: https://colab.research.google.com/drive/1yiXSwFafXpMLHaov9iBTQLIDZ6bK1zYX?usp=sharing
      - text: "Gene level: 16S rRNA detection"
        href: https://colab.research.google.com/drive/1G7bOFEX87cZNrM2tdRtTdkrZn5fM__g0?usp=sharing
      - text: "Genome level: Bacterial morphology (Sporulation)"
        href: https://colab.research.google.com/drive/1BCggL-tfQF136YeJ8cKKi-zoBEDMgkNh?usp=sharing  
      - text: "Full metagenome level: Colorectal cancer prediction" 
        href: https://colab.research.google.com/drive/10xpRzGd3JeBAbqQYSCxzQUMctt01sx9D?usp=sharing   
      - text: "BERT with deepG"
        href: https://colab.research.google.com/drive/1kyYK7IU7GSfdpDzO_a8U3_qD4i3zTu6w?usp=sharing  
    tutorials:
      text: Tutorials
      menu:
      - text: Getting Started
        href: articles/getting_started.html
      - text: Training types
        href: articles/training_types.html
      - text: Data generator
        href: articles/data_generator.html
      - text: Using tensorboard
        href: articles/using_tb.html
      - text: Integrated Gradient
        href: articles/integrated_gradient.html
reference:
- title: Training
  contents: 
  - train_model
  - train_model_cpc
  - resume_training_from_model_card
- title: Model Architecture
  contents:
  - starts_with("create_model_")
  - remove_add_layers
  - merge_models
  - get_output_activations
  - reshape_input
  - load_cp
  - compile_model
  - starts_with("layer_")
- title: Callbacks
  contents:
  - conf_matrix_cb
  - early_stopping_time_cb
  - validation_after_training_cb
  - reset_states_cb
  - remove_checkpoints
  - model_card_cb
- title: Metrics and Losses
  contents:
  - noisy_loss_wrapper
  - balanced_acc_wrapper
  - f1_wrapper
  - auc_wrapper
  - exp_decay
  - stepdecay
  - sgdr
  - focal_loss_multiclass
  - loss_cl
- title: Generators
  contents:
  - starts_with("generator_")
  - get_generator
  - dataset_from_gen
- title: Prediction
  contents:
  - predict_model
  - summarize_states
  - predict_with_n_gram
  - load_prediction
- title: Evaluation
  contents:
  - starts_with("evaluate_")
  - plot_roc
- title: Visualization
  contents:
  - integrated_gradients
  - heatmaps_integrated_grad
  - plot_cm
- title: Preprocessing
  contents:
  - seq_encoding_label
  - seq_encoding_lm
  - get_class_weight
  - get_start_ind
  - int_to_n_gram
  - n_gram_dist
  - n_gram_of_matrix
  - reshape_tensor
  - split_fasta
  - one_hot_to_seq
- title: Data
  contents:
  - crispr_sample
  - ecoli_small
  - parenthesis
- title: Dummy Data
  contents: create_dummy_data
- title: Session Management
  contents:
  - deepG

