| adjustedRandIndex | Adjusted Rand Index |
| AMRI | Adjusted Multi-resolution Rand Index between two clusterings |
| assign_samples_to_paths | Assign data points to the viable path that are closest to the... |
| augment_path | Augment the path to include on additional node as alternative... |
| clust_example | A array of simulated multi-resolution clustering, with... |
| consensus_clustering | Perform consensus clustering |
| consensus_clustering_weighted | weighted consensus clustering |
| consensus_clustering_within_resolution | Perform consensus clustering among clusterings of same number... |
| construct_tree_from_labelmat | Construct the cluster tree from multi-resolution clustering... |
| cost | Calculate the cost generate by adding the edge = (start, end)... |
| create_sce_from_counts | Create SingleCellExperiment object from count data |
| create_sce_from_normcounts | Create SingleCellExperiment object from normalized data |
| data_example | A simulated single cell RNAseq data of 500 genes-by-500... |
| decode | parse the node name as the layer and cluster |
| diff_between_similarity_mat | Calculate the L1 distance between two similarity matrix. Get... |
| div_0 | pointwise division of matrices such that 0/0=0 |
| expected_MRI_perm | expected Multi-resolution Rand Index (MRI) under random... |
| exponential_sampling | Exponential sampling |
| generateDataSymSim | Generate single cell data using SymSim model |
| get_bad_nodeset | Output the set of bad node in the given tree |
| get_index | Calculate the index between two clusterings |
| get_index_per_layer | Calculate the similarity between each layer of initial... |
| getmode | Get the mode in the vector |
| get_set_D_size | get the size of set D, pairs that are in different clusters... |
| get_similarity_from_labelmat | Get sample pairwise similarity matrix from the label matrix |
| get_similarity_from_tree | Calculate the pairwise similarity matrix between samples,... |
| gg_color_hue | Generate colors that approximate the default ggplot colors |
| grid_interpolant_next | Grid intepolation using the next value |
| hamming.distance | Hamming Distances of Vectors |
| label_onehot | one-hot code the label vector |
| label_to_membership | Convert label vector to membership matrix |
| linear_sampling | Linear sampling. |
| modularity | Modularity function given the adjacency matrix |
| modularity_event_sampling | Event sample method for resolution parameters of modularity... |
| mrtree | Muti-resolution reconciled tree (MRtree) |
| path_dot_product | outer product of path prefix and suffix |
| plot_clustree | Plot MRtree results as a dendrogram. If reference labels are... |
| plotContTable | Plot the confusion matrix via heatmap, with true labels in... |
| plot_tree | Plot MRtree results as hierarchical cluster tree. |
| plot_umap | UMAP plot |
| prune_paths | Remove the paths that include the same node.end but different... |
| prune_tree | Prune the dendrogram to have the specified number of clusters |
| random_tree | Generate a random tree with even number of tips |
| rep_mat | repeat the vector as a matrix |
| sc_clustering.HAC | Perform Single Cell data clustering using Hierarchical... |
| sc_clustering.sc3 | Perform Single Cell data clustering using SC3 clustering... |
| sc_clustering.seurat | Perform Single Cell data clustering using Seurat |
| sc_clustering.simlr | Perform Single Cell data clustering using SIMLR |
| sc_clustering.soup | Perform Single Cell data clustering using SOUP |
| sc_clustering.umap_kmeans | Perform Single Cell data clustering using UMAP+kmeans |
| seurat_get_nn_graph | Get the nearest neighbor graph using Seurat |
| stability_plot | Stability analysis that measures the similarity between the... |
| table_to_edgelist | Convert the start end table to an edgelist |
| tree1 | Generate tree structure |
| tree_to_labelmat | Convert phylo_tree to label matrix |
| tree_to_labelmat.hclust | Convert hclust tree to label matrix |
| tree_to_labelmat.phylo | Convert phylo tree to labelmatrix |
| unique_ind | Get the unique values in the matrix |
