BoBa-T

Getting started

  • Installation
    • System requirements
    • Dependencies
    • Installing BoBa-T

Tutorials

  • Tutorials
    • 0. Input data
    • 1. Building a base network structure
      • Network Construction and Feature Selection with BoBa-T
        • Setup and Imports
        • Configure Paths
        • Part 1: Load and Explore DIRECT-NET Data
        • Part 2: Build Initial Network
        • Part 3: Load Expression Data
        • Part 4: LASSO Feature Selection
        • Part 5: Compare Networks Across Alpha Values
        • Part 6: Adaptive LASSO Pruning
        • Part 7: Visualize Network Changes
        • Bonus: Export for Boolean Modeling
      • Base network from ChEA databases (BooleaBayes)
        • Setup and imports
        • Configure paths and transcription factors
        • Query enrichment databases for each TF’s targets
        • Restrict to ChEA-sourced interactions
        • Build the transcription-factor network
        • Prune the network
        • Save the base network
        • Next step
    • 2. Inferring network rules
      • Boba-T Example for Beta Cell Differentiation scRNAseq Data
        • Load Network
        • Load Data and Clusters & Split into Training and Testing Sets
        • Binarize data
        • Fit rules with training dataset
        • Perform Cross Validation and Plot Accuracy Metrics
        • Get attractors
        • Perturbations
      • Rule inference from two timepoints
        • Setup and imports
        • Configure paths
        • Load network and both timepoints
        • Split into training/test, keeping timepoints paired
        • Binarize
        • Fit rules using the paired timepoints
        • Next steps
      • Rule inference from pseudotime
        • Setup and imports
        • Configure paths
        • Load network and data
        • Build the next-state matrix from velocity/pseudotime
        • Fit rules from the ordering
        • Next steps
    • 3. Finding attractors
      • Finding attractors
        • Setup and imports
        • Configure paths
        • Load network, rules, and binarized data
        • Search for attractors
        • Filter attractors to the relevant ones
        • Visualize attractors
        • Load the attractor dictionary for downstream use
        • Next step
    • 4. In silico perturbations
      • In silico perturbations
        • Setup and imports
        • Configure paths
        • Load network, rules, and attractors
        • Run perturbation random walks
        • Summarize perturbation effects
        • Per-gene and destabilization plots
        • Related
    • Validation and downstream analysis
      • Validating rule accuracy
        • Setup and imports
        • Configure paths
        • Load network, rules, and the test set
        • Score the test set and compute ROC/AUC per node
        • Plot AUCs and averaged ROC
        • scikit-learn classification metrics
      • Random walks and plotting trajectories
        • Setup and imports
        • Configure paths
        • Load network, rules, and attractors
        • Run random walks
        • Plot trajectories
        • Attractor stability
        • Related

API reference

  • API reference
    • net — network structure
      • prune()
      • prune_info()
      • prune_to_chea()
      • make_network()
      • save_network()
      • add_connections()
      • build_network_from_directnet()
      • lasso_feature_selection()
      • compare_networks()
      • adaptive_lasso_pruning()
    • load — loading data
      • load_network()
      • prune_network()
      • load_data()
      • load_data_multiple()
      • load_rules()
    • proc — processing
      • binarize_data()
    • rw — random walk
      • random_walks()
      • random_walks_parallel()
      • simple_random_walk()
      • random_walk_until_leave_basin()
      • random_walk_until_reach_basin()
      • long_random_walks()
    • tl — tools
      • reorder_binary_decision_tree()
      • detect_irrelevant_regulator()
      • get_rules_scvelo()
      • get_rules()
      • save_rules()
      • parent_heatmap()
      • roc()
      • calc_roc()
      • auc()
      • save_auc_by_gene()
      • fit_validation()
      • roc_from_file()
      • get_sklearn_metrics()
      • get_sample_avg_curve()
      • plot_cohort_roc_with_ci()
      • find_attractors()
      • write_attractor_dict()
      • filter_attractors()
      • find_avg_states()
      • perturbations_summary()
    • plot — plotting
      • plot_sklearn_summ_stats()
      • plot_sklearn_metrics()
      • plot_roc()
      • plot_aucs()
      • plot_validation_avgs()
      • parent_heatmap()
      • plot_accuracy()
      • plot_attractors()
      • plot_attractors_clustermap()
      • make_jaccard_heatmap()
      • plot_rule()
      • plot_histograms()
      • plot_destabilization_scores()
      • plot_perturb_gene_dictionary()
      • plot_stability()
      • plot_random_walks()
      • pca_plot_paths()
      • plot_all_random_walks()
      • check_middle_stop()
      • draw_grn()
      • plot_subgraph()
    • utils — utilities
      • make_color_map()
      • binarized_umap_transform()
      • binarized_data_dict_to_binary_df()
      • binarize_data_df()
      • idx2binary()
      • state2idx()
      • state_bool2idx()
      • hamming()
      • hamming_idx()
      • r2()
      • split_train_test()
      • split_train_test_crossval()
      • condense()
      • average_state()
      • inspect_state()
      • update_node()
      • prune_stg_edges()
      • get_nodes()
      • get_clusters()
      • get_leaves_of_regulator()
      • get_avg_state_index()
      • get_reprogramming_rules()
      • get_flip_probs()
      • get_avg_min_distance()
      • get_attractors()
      • get_partial_stg()
      • get_ci_sig()
      • get_perturbation_dict()
      • reverse_dictionary()
      • reverse_perturb_dictionary()
      • write_dict_of_dicts()
      • get_attractor_dict()
      • print_graph_info()
    • enrichr — enrichment
      • get_libraries()
      • amax()
      • amin()
      • query_gene()
      • submit_gene_list()
      • enrich()
      • process_background()
      • process_chea_lists()
      • build_tf_network()
      • prune_weak_edges()
      • get_chea_source()
      • get_transfac_source()
      • get_targetscan_source()
      • get_browser_source()
      • get_encode_source()
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