Man pages for saeyslab/nichenetr
Modeling Intercellular Communication by Linking Ligands to Target Genes with NicheNet
| add_hyperparameters_parameter_settings | Add hyperparameters to existing parameter settings |
| add_ligand_popularity_measures_to_perfs | Merge target gene prediction performances with popularity... |
| add_new_datasource | Add a new data source to the model |
| alias_to_symbol_seurat | Convert aliases to official gene symbols in a Seurat Object |
| annotation_data_sources | Annotation table of all data sources used in the NicheNet... |
| apply_hub_corrections | Apply hub corrections to the weighted integrated... |
| assess_influence_source | Assess the influence of an individual data source on... |
| assess_rf_class_probabilities | Assess probability that a target gene belongs to the geneset... |
| assign_ligands_to_celltype | Assign ligands to cell types |
| bootstrap_ligand_activity_analysis | Run ligand activity analysis with bootstrap |
| calculate_de | Calculate differential expression of one cell type versus all... |
| calculate_fraction_top_predicted | Determine the fraction of genes belonging to the geneset or... |
| calculate_fraction_top_predicted_fisher | Perform a Fisher's exact test to determine whether genes... |
| calculate_niche_de | Calculate differential expression of cell types in one niche... |
| calculate_niche_de_targets | Calculate differential expression of receiver cell type in... |
| calculate_p_value_bootstrap | Calculate ligand p-values from the bootstrapped ligand... |
| calculate_spatial_DE | Calculate differential expression between spatially different... |
| classification_evaluation_continuous_pred_wrapper | Assess how well classification predictions accord to the... |
| combine_sender_receiver_de | Combine the differential expression information of ligands in... |
| construct_ligand_target_matrix | Construct a ligand-target probability matrix for ligands of... |
| construct_ligand_tf_matrix | Construct a ligand-tf signaling probability matrix for... |
| construct_model | Construct a ligand-target model given input parameters. |
| construct_random_model | Construct a randomised ligand-target model given input... |
| construct_tf_target_matrix | Construct a tf-target matrix. |
| construct_weighted_networks | Construct weighted layer-specific networks |
| convert_alias_to_symbols | Convert aliases to official gene symbols |
| convert_cluster_to_settings | Convert cluster assignment to settings format suitable for... |
| convert_expression_settings_evaluation | Convert expression settings to correct settings format for... |
| convert_expression_settings_evaluation_regression | Convert expression settings to correct settings format for... |
| convert_gene_list_settings_evaluation | Convert gene list to correct settings format for evaluation... |
| convert_human_to_mouse_symbols | Convert human gene symbols to their mouse one-to-one... |
| convert_mouse_to_human_symbols | Convert mouse gene symbols to their human one-to-one... |
| convert_settings_ligand_prediction | Convert settings to correct settings format for ligand... |
| convert_settings_tf_prediction | Convert settings to correct settings format for TF... |
| convert_settings_topn_ligand_prediction | Converts expression settings to format in which the total... |
| convert_single_cell_expression_to_settings | Prepare single-cell expression data to perform ligand... |
| correct_topology_ppr | Adapt a ligand-target probability matrix construced via PPR... |
| diagrammer_format_signaling_graph | Prepare extracted ligand-target signaling network for... |
| estimate_source_weights_characterization | Estimate data source weights of data sources of interest... |
| evaluate_importances_ligand_prediction | Evaluation of ligand activity prediction based on ligand... |
| evaluate_ligand_prediction_per_bin | Evaluate ligand activity predictions for different... |
| evaluate_model | Construct and evaluate a ligand-target model given input... |
| evaluate_model_application | Construct and evaluate a ligand-target model given input... |
| evaluate_model_application_multi_ligand | Construct and evaluate a ligand-target model given input... |
| evaluate_model_cv | Construct and evaluate a ligand-target model given input... |
| evaluate_multi_ligand_target_prediction | Evaluation of target gene prediction for multiple ligands. |
| evaluate_multi_ligand_target_prediction_regression | Evaluation of target gene value prediction for multiple... |
| evaluate_random_model | Construct and evaluate a randomised ligand-target model given... |
| evaluate_single_importances_ligand_prediction | Evaluation of ligand activity prediction performance of... |
| evaluate_target_prediction | Evaluation of target gene prediction. |
| evaluate_target_prediction_interprete | Evaluation of target gene prediction. |
| evaluate_target_prediction_per_bin | Evaluate target gene predictions for different bins/groups of... |
| evaluate_target_prediction_regression | Evaluation of target gene value prediction (regression). |
| expression_settings_validation | Expression datasets for validation |
| extract_ligands_from_settings | Extract ligands of interest from settings |
| extract_top_fraction_ligands | Get the predicted top n percentage ligands of a target of... |
| extract_top_fraction_targets | Get the predicted top n percentage target genes of a ligand... |
| extract_top_n_ligands | Get the predicted top n ligands of a target gene of interest |
| extract_top_n_targets | Get the predicted top n target genes of a ligand of interest |
| geneinfo_2022 | Gene annotation information: version 2 - january 2022 |
| geneinfo_alias_human | Gene annotation information: version 2 - january 2022 -... |
| geneinfo_alias_mouse | Gene annotation information: version 2 - january 2022 -... |
| geneinfo_human | Gene annotation information |
| generate_info_tables | Generate tables used for 'generate_prioritization_tables' |
| generate_prioritization_tables | Perform a prioritization of cell-cell interactions (similar... |
| get_active_ligand_receptor_network | Get active ligand-receptor network for cellular interaction... |
| get_active_ligand_target_df | Get active ligand-target network in data frame format. |
| get_active_ligand_target_matrix | Get active ligand-target matrix. |
| get_active_regulatory_network | Get active gene regulatory network in a receiver cell. |
| get_active_signaling_network | Get active signaling network in a receiver cell. |
| get_expressed_genes | Determine expressed genes of a cell type from an input object |
| get_exprs_avg | Calculate average of gene expression per cell type. |
| get_lfc_celltype | Get log fold change values of genes in cell type of interest |
| get_ligand_activities_targets | Calculate the ligand activities and infer ligand-target links... |
| get_ligand_signaling_path | Get ligand-target signaling paths between ligand(s) and... |
| get_ligand_signaling_path_with_receptor | Get ligand-target signaling paths between ligand(s),... |
| get_ligand_slope_ligand_prediction_popularity | Regression analysis between popularity of left-out ligands... |
| get_ligand_target_links_oi | Get ligand-target links of interest |
| get_multi_ligand_importances | Get ligand importances from a multi-ligand classfication... |
| get_multi_ligand_importances_regression | Get ligand importances from a multi-ligand regression model. |
| get_multi_ligand_rf_importances | Get ligand importances from a multi-ligand trained random... |
| get_multi_ligand_rf_importances_regression | Get ligand importances from a multi-ligand trained random... |
| get_ncitations_genes | Get the number of times of gene is mentioned in the pubmed... |
| get_non_spatial_de | Makes a table similar to the output of 'calculate_spatial_DE'... |
| get_optimized_parameters_nsga2r | Get optimized parameters from the output of... |
| get_prioritization_tables | Use the information from the niche- and spatial differential... |
| get_single_ligand_importances | Get ligand importances based on target gene prediction... |
| get_single_ligand_importances_regression | Get ligand importances based on target gene value prediction... |
| get_slope_ligand_popularity | Regression analysis between ligand popularity and target gene... |
| get_slope_target_gene_popularity | Regression analysis between target gene popularity and target... |
| get_slope_target_gene_popularity_ligand_prediction | Regression analysis between target gene popularity and ligand... |
| get_target_genes_ligand_oi | Get a set of predicted target genes of a ligand of interest |
| get_top_predicted_genes | Find which genes were among the top-predicted targets genes... |
| get_weighted_ligand_receptor_links | Get the weighted ligand-receptor links between a possible... |
| get_weighted_ligand_target_links | Infer weighted active ligand-target links between a possible... |
| gr_network | Gene regulatory network |
| hyperparameter_list | Optimized hyperparameter values |
| infer_supporting_datasources | Get the data sources that support the specific interactions... |
| ligand_activity_performance_top_i_removed | Calculate ligand activity performance without considering... |
| lr_network | Ligand-receptor network |
| make_circos_lr | make_circos_lr |
| make_circos_plot | Draw a circos plot |
| make_discrete_ligand_target_matrix | Convert probabilistic ligand-target matrix to a discrete one. |
| make_heatmap_bidir_lt_ggplot | Make a ggplot heatmap object from an input ligand-target... |
| make_heatmap_ggplot | Make a ggplot heatmap object from an input matrix (2-color). |
| make_ligand_activity_target_exprs_plot | make_ligand_activity_target_exprs_plot |
| make_ligand_receptor_lfc_plot | make_ligand_receptor_lfc_plot |
| make_ligand_receptor_lfc_spatial_plot | make_ligand_receptor_lfc_spatial_plot |
| make_line_plot | Make a line plot |
| make_mushroom_plot | Make a "mushroom plot" of ligand-receptor interactions |
| make_threecolor_heatmap_ggplot | Make a ggplot heatmap object from an input matrix (3-color). |
| mlrmbo_optimization | Optimization of objective functions via model-based... |
| model_based_ligand_activity_prediction | Prediction of ligand activity prediction by a model trained... |
| model_evaluation_hyperparameter_optimization_mlrmbo | Construct and evaluate a ligand-target model given input... |
| model_evaluation_optimization_application | Construct and evaluate a ligand-target model given input... |
| model_evaluation_optimization_mlrmbo | Construct and evaluate a ligand-target model given input... |
| model_evaluation_optimization_nsga2r | Construct and evaluate a ligand-target model with the purpose... |
| mutate_cond | Change values in a tibble if some condition is fulfilled. |
| ncitations | Number of citations for genes |
| nichenetr-package | nichenetr: Modeling Intercellular Communication by Linking... |
| nichenet_seuratobj_aggregate | Perform NicheNet analysis on Seurat object: explain DE... |
| nichenet_seuratobj_aggregate_cluster_de | Perform NicheNet analysis on Seurat object: explain DE... |
| nichenet_seuratobj_cluster_de | Perform NicheNet analysis on Seurat object: explain DE... |
| normalize_single_cell_ligand_activities | Normalize single-cell ligand activities |
| optimized_source_weights_df | Optimized data source weights |
| predict_ligand_activities | Predict activities of ligands in regulating expression of a... |
| predict_single_cell_ligand_activities | Single-cell ligand activity prediction |
| prepare_circos_visualization | Prepare circos visualization |
| prepare_ligand_receptor_visualization | Prepare ligand-receptor visualization |
| prepare_ligand_target_visualization | Prepare heatmap visualization of the ligand-target links... |
| prepare_settings_leave_one_in_characterization | Prepare settings for leave-one-in characterization |
| prepare_settings_leave_one_out_characterization | Prepare settings for leave-one-out characterization |
| prepare_settings_one_vs_one_characterization | Prepare settings for one-vs-one characterization |
| process_characterization_ligand_prediction | Process the output of model evaluation for data source... |
| process_characterization_ligand_prediction_single_measures | Process the output of model evaluation for data source... |
| process_characterization_popularity_slopes_ligand_prediction | Process the output of model evaluation for data source... |
| process_characterization_popularity_slopes_target_prediction | Process the output of model evaluation for data source... |
| process_characterization_target_prediction | Process the output of model evaluation for data source... |
| process_characterization_target_prediction_average | Process the output of model evaluation for data source... |
| process_mlrmbo_nichenet_optimization | Process the output of mlrmbo multi-objective optimization to... |
| process_niche_de | Process the DE output of 'calculate_niche_de' |
| process_receiver_target_de | Processing differential expression output of the receiver... |
| process_spatial_de | Process the spatialDE output |
| process_table_to_ic | Process DE or expression information into intercellular... |
| randomize_complete_network_source_specific | Randomize an integrated network by shuffling its source... |
| randomize_datasource_network | Randomize a network of a particular data source. |
| randomize_network | Randomize a network |
| run_nsga2R_cluster | Run NSGA-II for parameter optimization. |
| scale_quantile | Cut off outer quantiles and rescale to a [0, 1] range |
| scale_quantile_adapted | Normalize values in a vector by quantile scaling and add a... |
| scaling_modified_zscore | Normalize values in a vector by the modified z-score method. |
| scaling_zscore | Normalize values in a vector by the z-score method |
| sig_network | Signaling network |
| single_ligand_activity_score_classification | Assess how well cells' ligand activities predict a binary... |
| single_ligand_activity_score_regression | Perform a correlation and regression analysis between cells'... |
| source_weights_df | Data source weights |
| visualize_parameter_values | Visualize parameter values from the output of... |
| visualize_parameter_values_across_folds | Visualize parameter values from the output of... |
| wrapper_average_performances | Calculate average performance of datasets of a specific... |
| wrapper_evaluate_single_importances_ligand_prediction | Evaluation of ligand activity prediction performance of... |
