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