SMODER

Main contents

  • Installation
    • Requirements
    • Install from PyPI
    • Install from GitHub
    • Create a Python environment
    • Current recommended execution method
    • Data preparation
  • Data
    • Required input files
    • Example directory layout
    • How to obtain the data
    • How to prepare data
    • Example
    • Notes
  • Tutorials
    • SMODER Tutorial 01: Mouse Brain H3K27ac Quick Start
      • Before you begin
      • Step 1. Define tutorial settings
      • Step 2. Review configuration
      • Step 3. Check required input files
      • Step 4. Load input data
      • Step 5. Initialize the model and preprocess the data
      • Step 6. Perform feature engineering and graph construction
      • Step 7. Optional model training
      • Step 8. Save results
      • Step 9. Inspect output directory
      • Step 10. Preview the cell type proportions
      • Step 11. Inspect result object metadata
      • Summary
      • Next steps
    • SMODER Tutorial 02: Mouse Brain H3K27ac Result Visualization
      • What is spatial_decon_result.h5ad?
      • Load the SMODER result
      • Plot cell-type proportion heatmaps
      • Plot spatial clusters from learned embeddings
      • Reconstruct denoised RNA marker expression
      • Reconstruct denoised gene-level epigenomic signals
      • Complete plotting script
      • Representative results
        • Cell-type proportion heatmaps
        • Spatial clustering from learned embeddings
        • Denoised RNA marker heatmaps
        • Denoised gene-level epigenomic signal heatmaps
    • SMODER Tutorial 03: Simulated Human Melanoma Result Visualization
      • What is spatial_decon_result.h5ad?
      • Load the SMODER result
      • Extract spatial coordinates and proportions
      • Plot proportion heatmaps
      • Complete plotting script
      • Representative results
        • All cell-type proportion heatmaps
        • Compact proportion panel
      • Notes
    • SMODER Tutorial 04: HBC Result Visualization
      • What is spatial_decon_result.h5ad?
      • Load the SMODER result
      • Plot cell-type proportion heatmaps
      • Plot spatial clusters from learned embeddings
      • Reconstruct denoised RNA marker expression
      • Reconstruct denoised ADT marker signals
      • Complete plotting script
      • Representative results
        • Cell-type proportion heatmaps
        • Spatial clustering from learned embeddings
        • Denoised RNA marker heatmaps
        • Denoised ADT marker heatmaps
  • API Reference
    • Core model
      • selectInfoGenes()
      • SpaMultiDecon_two_modals
        • SpaMultiDecon_two_modals.weight_loss
        • SpaMultiDecon_two_modals.hidden_dim
        • SpaMultiDecon_two_modals.learning_rate
        • SpaMultiDecon_two_modals.device
        • SpaMultiDecon_two_modals.epochs
        • SpaMultiDecon_two_modals.seed
        • SpaMultiDecon_two_modals.weight_spatial
        • SpaMultiDecon_two_modals.weight_consistency
        • SpaMultiDecon_two_modals.pca_n_components_rna
        • SpaMultiDecon_two_modals.modal2_target_dim
        • SpaMultiDecon_two_modals.lsi_random_state
        • SpaMultiDecon_two_modals.set_nn_para()
        • SpaMultiDecon_two_modals.preprocess()
        • SpaMultiDecon_two_modals.run_feature_engineering_and_mapping()
        • SpaMultiDecon_two_modals.create_spatialgraph()
        • SpaMultiDecon_two_modals.get_laplacian()
        • SpaMultiDecon_two_modals.create_featuregraph()
        • SpaMultiDecon_two_modals.train()
    • Pipelines
      • set_base_config()
      • set_analysis_params()
      • load_and_show_data()
      • init_model_and_preprocess()
      • feature_engineering_and_graph_build()
      • train_model()
      • clean_anndata_for_save()
      • save_results()
      • main()
    • Preprocessing
      • RNA preprocessing
        • filter_out_low_quality_data()
        • process_single_cell()
        • process_single_cell_path()
        • sanitize_filename()
        • normalize_expression_matrix()
        • normalize_single_cell()
        • process_spatial_data()
        • process_spatial_data_path()
        • get_spatial_hvgs_only()
        • select_hvgs()
        • calculate_celltype_averages()
        • calculate_celltype_averages2()
      • Second-modality preprocessing
        • clr_normalization()
        • process_spatial_adt_data()
        • process_spatial_adt_data_path()
        • process_peak_data()
        • process_peak_data_path()
    • Postprocessing
      • Reconstruction
        • set_random_seed()
        • normalize_coords()
        • standardize_embedding()
        • lognorm_transform()
        • filter_valid_genes()
        • load_align_data()
        • project_coords()
        • RNAFCModel
        • rna_run()
        • second_modality_preprocess_single()
        • second_modality_preprocess_batch()
        • DenseGCNConv
        • SecondModalityGCNModel
        • build_spatial_adj()
        • second_modality_run()
        • omics_reconstruct()
    • Visualization
      • Spatial visualization
        • get_spatial_xy()
        • save_spatial_continuous()
        • save_spatial_categorical()
        • get_cell_type_proportions()
        • sanitize_filename()
        • plot_cell_type_proportion_panel()
        • plot_all_cell_type_proportions()
        • plot_individual_cell_type_heatmaps()
        • plot_embedding_spatial_clustering()
        • plot_reconstruction_heatmaps()
    • Configuration
      • get_mousebrain_h3k27ac_base_config()
      • get_mousebrain_h3k27ac_params()
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