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| aggregate_gene_expression | Creates a matrix with aggregated expression values for arbitrary groups of genes |
| align_cds | Align cells from different groups within a cds |
| calc_principal_graph | Function to automatically learn the structure of data by either using L1-graph or the spanning-tree formulization |
| cell_data_set | The cell_data_set class |
| cell_data_set-class | The cell_data_set class |
| cell_data_set-methods | Methods for the cell_data_set class |
| choose_cells | Choose cells interactively to subset a cds |
| choose_graph_segments | Choose cells along the path of a principal graph |
| clear_cds_slots | Clear CDS slots |
| clusters | Generic to extract clusters from CDS object |
| clusters-method | Method to extract clusters from CDS object |
| cluster_cells | Cluster cells using Louvain/Leiden community detection |
| coefficient_table | Extracts a table of coefficients from a tibble containing model objects |
| combine_cds | Combine a list of cell_data_set objects |
| compare_models | Compares goodness of fit for two ways of fitting a set of genes' expression |
| detect_genes | Detects genes above minimum threshold. |
| estimate_size_factors | Function to calculate size factors for single-cell RNA-seq data |
| evaluate_fits | Evaluate the fits of model objects. |
| exprs | Generic to access cds count matrix |
| exprs-method | Method to access cds count matrix |
| fData | Generic to access cds rowData table |
| fData-method | Generic to access cds rowData table |
| fData<- | Generic to set cds rowData table |
| fData<--method | Method to set cds rowData table |
| find_gene_modules | Cluster genes into modules that are co-expressed across cells. |
| fit_models | Fits a model for each gene in a cell_data_set object. |
| generate_centers | Function to reproduce the behavior of eye function in matlab |
| generate_garnett_marker_file | Generate a Garnett marker file from top_markers output. |
| get_citations | Access citations for methods used during analysis. |
| get_genome_in_matrix_path | Get a genome from Cell Ranger output |
| graph_test | Test genes for differential expression based on the low dimensional embedding and the principal graph |
| learn_graph | Learn principal graph from the reduced dimension space using reversed graph embedding |
| load_a549 | Build a cell_data_set from the data stored in inst/extdata directory. |
| load_cellranger_data | Load data from the 10x Genomics Cell Ranger pipeline |
| load_mm_data | Load data from matrix market format files. |
| load_mtx_data | Load data from matrix market format |
| mc_es_apply | Multicore apply-like function for cell_data_set |
| model_predictions | Predict output of fitted models and return as a matrix |
| new_cell_data_set | Create a new cell_data_set object. |
| normalized_counts | Return a size-factor normalized and (optionally) log-transformed expression matrix |
| order_cells | Orders cells according to pseudotime. |
| partitions | Generic to extract partitions from CDS object |
| partitions-method | Method to extract partitions from CDS object |
| pData | Generic to access cds colData table |
| pData-method | Method to access cds colData table |
| pData<- | Generic to set cds colData table |
| pData<--method | Method to set cds colData table |
| plot_cells | Plots the cells along with their trajectories. |
| plot_cells_3d | Plot a dataset and trajectory in 3 dimensions |
| plot_genes_by_group | Create a dot plot to visualize the mean gene expression and percentage of expressed cells in each group of cells |
| plot_genes_in_pseudotime | Plots expression for one or more genes as a function of pseudotime |
| plot_genes_violin | Plot expression for one or more genes as a violin plot |
| plot_pc_variance_explained | Plots the percentage of variance explained by the each component based on PCA from the normalized expression data determined using preprocess_cds. |
| plot_percent_cells_positive | Plots the number of cells expressing one or more genes above a given value as a barplot |
| preprocess_cds | Preprocess a cds to prepare for trajectory inference |
| principal_graph | Generic to extract principal graph from CDS |
| principal_graph-method | Method to extract principal graph from CDS |
| principal_graph<- | Generic to set principal graph to CDS |
| principal_graph<--method | Generic to set principal graph to CDS |
| principal_graph_aux | Generic to extract principal graph auxiliary information from CDS |
| principal_graph_aux-method | Method to extract principal graph auxiliary information from CDS |
| principal_graph_aux<- | Generic to set principal graph auxiliary information into CDS |
| principal_graph_aux<--method | Method to set principal graph auxiliary information into CDS |
| pseudotime | Generic to extract pseudotime from CDS object |
| pseudotime-method | Method to extract pseudotime from CDS object |
| reduce_dimension | Compute a projection of a cell_data_set object into a lower dimensional space with non-linear dimension reduction methods |
| repmat | function to reproduce the behavior of repmat function in matlab to replicate and tile an matrix |
| size_factors | Get the size factors from a cds object. |
| size_factors<- | Set the size factor values in the cell_data_set |
| soft_assignment | Function to calculate the third term in the objective function |
| sparse_prcomp_irlba | Principal Components Analysis |
| top_markers | Identify the genes most specifically expressed in groups of cells |