| adjacent_timepoint_auc | Compute adjacent-timepoint AUC for a pseudotime ordering |
| aggregate_pseudobulk | Aggregate single-cell data into pseudobulk samples |
| anticausal_edge_mass | Measure the weight of anti-causal edges in a directed graph |
| BenchmarkIntegration | Benchmark integration quality with scIB-inspired metrics |
| branch_onset_metrics | Measure branch-emergence timing from pseudotime |
| build_knn_graph | Build a cell-cell kNN graph |
| build_tata_graph | Build the TATA cluster graph |
| cluster_graph_states | Cluster graph-connected cell states |
| cluster_tata_gene_trends | Cluster TATA gene trends by shape |
| compute_tata_branch_probabilities | Compute TATA branch probabilities and entropy |
| compute_tata_gene_trends | Compute branch-specific TATA gene trends |
| compute_tata_pseudotime | Compute TATA pseudotime |
| compute_time_weights | Compute time consistency for cluster-cluster edges |
| compute_topology_weights | Compute topology-based cluster connectivity weights |
| CreateBacObject | Create a standardized bacterial single-cell object |
| directed_reachability_concordance | Quantify how well a directed cluster graph follows real time |
| FilterBacCells | Filter cells using bacterial QC thresholds |
| filter_pseudobulk_samples | Filter pseudobulk samples by size |
| IntegrateBacData | Integrate microbial single-cell batches |
| local_temporal_order_metrics | Compute local temporal order metrics on a cell graph |
| MergeBacObjects | Merge multiple scProkaR or SingleCellExperiment objects |
| normalize_pseudobulk | Normalize pseudobulk samples for exploratory analysis |
| orient_pseudotime_to_time | Orient pseudotime to match increasing real time |
| PlotIntegrationOverview | Plot Seurat-style integration result panels |
| PlotReduction | Plot any stored reduced dimension |
| plot_pairwise_de_ma | Plot an MA plot for a pairwise edgeR contrast |
| plot_pairwise_de_volcano | Plot a volcano plot for a pairwise edgeR contrast |
| plot_tata_branch_confusion | Plot truth versus inferred TATA branch assignments |
| plot_tata_branch_probabilities | Plot TATA branch probabilities on an embedding |
| plot_tata_branch_selection | Plot selected cells from one TATA branch |
| plot_tata_cluster_graph | Plot the cluster-level TATA graph |
| plot_tata_edge_causality | Plot TATA edge causality diagnostics |
| plot_tata_gene_trends | Plot fitted TATA gene trends |
| plot_tata_gene_trend_heatmap | Plot a heatmap of TATA gene trends |
| plot_tata_results | Plot an overview of TATA results |
| plot_tata_terminal_probabilities | Plot branch probabilities for representative cells |
| plot_tata_time_calibration | Plot TATA time calibration |
| plot_tata_trajectory_embedding | Plot TATA trajectories over an embedding |
| plot_time_series_deg_curves | Plot fitted spline expression curves from time-series DE |
| RegisterExistingIntegrationEmbeddings | Register existing reduced dimensions as integration embeddings |
| RegisterIntegrationEmbedding | Register an external embedding for benchmarking and downstream analysis |
| RunBacQC | Compute bacterial QC metrics |
| RunIntegratedClustering | Cluster cells on an integrated embedding |
| RunIntegratedUMAP | Run UMAP on an existing embedding |
| run_edger_pairwise_de | Run pairwise pseudobulk differential expression with edgeR |
| run_edger_spline_de | Run pseudobulk spline or time-series differential expression with edgeR |
| run_scproka_de | Run a full scProkaR differential expression workflow |
| run_tata | Run the full TATA workflow |
| sce1 | Example bacterial single-cell dataset |
| select_tata_branch_cells | Select cells from a TATA branch |
| simulate_tata_divergent_sce | Simulate a divergent TATA dataset |
| simulate_tata_multidrug_sce | Simulate a multi-drug branching TATA dataset |
| simulate_tata_sce | Simulate a divergent TATA dataset |
| simulate_tata_spiral_sce | Simulate an extreme spiral-plus-divergent TATA dataset |