An Umbrella Framework for Multi-Source and Multi-Omics
Clustering
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Documentation for package ‘MosaiClusteR’ version 0.1.0
Help Pages
| ABCdeep.SingleInMultiple | Single-source ABC with a deep-learning (autoencoder) Step 4 (ABCdeep) |
| ABCdist.SingleInMultiple | Single-source ABC with distance accumulation |
| ABCpp.SingleInMultiple | Single-source Aggregating Bundles of Clusters (ABC), C++-accelerated engine |
| ADC | Aggregated data clustering |
| ADEC | Aggregated data ensemble clustering |
| BinFeaturesPlot_MultipleData | Visualization of characteristic binary features of multiple data sets |
| BinFeaturesPlot_SingleData | Visualization of characteristic binary features of a single data set |
| BoxPlotDistance | Box plots of one distance matrix categorized against another distance matrix. |
| CEC | Complementary ensemble clustering |
| CharacteristicFeatures | Determine the characteristic features of clusters |
| characterize_clusters | Characterise clusters with external (biological / clinical) variables |
| ChooseCluster | Interactive plot to determine DE Genes and DE features for a specific cluster |
| Cluster | Single-source base clustering |
| ClusterCols | Helper that colours dendrogram leaves by cluster membership |
| ClusteringAggregation | Clustering aggregation |
| clustering_concordance | Compare clustering solutions to each other (no ground truth needed) |
| ClusterPlot | Colouring clusters in a dendrogram |
| cluster_agreement | Agreement between two partitions |
| cluster_biology_panel | Panel of cluster characterisation plots |
| cluster_k_sweep | Show the clustering at every k (see how it deteriorates) |
| cluster_selection_plot | Justify the number of clusters (silhouette + elbow / scree) |
| ColorPalette | Create a color palette to be used in the plots |
| ColorsNames | Function that annotates colors to their names |
| CompareInteractive | Interactive comparison of single and multiple source clustering results |
| ComparePlot | Comparison of clustering results over multiple methods |
| CompareSilCluster | Compares medoid clustering results based on silhouette widths |
| CompareSvsM | Comparison of clustering results for the single and multiple source clustering. |
| compare_clusterings | Compare two clusterings derived from distance matrices |
| compare_methods_plot | Visually compare clustering solutions with ComparePlot (no ground truth) |
| ConsensusClustering | Voting-based consensus clustering |
| ContFeaturesPlot | Plot of continuous features |
| create_data_nuggets | Create data nuggets from a data matrix |
| CVAA | Cumulative Voting Aggregation (CVAA / W-CVAA) |
| Cyclogram | Comparison of clustering results over multiple results in circular format |
| DetermineWeight_SilClust | Determines an optimal weight for weighted clustering by silhouettes widths. |
| DetermineWeight_SimClust | Determines an optimal weight for weighted clustering by similarity weighted clustering. |
| DiffGenes | Find differentially expressed genes |
| DiffGenesSelection | Differential expression for a selection of objects |
| Distance | Compute a distance matrix |
| distanceheatmaps | Determine the distance in a heatmap |
| Distance_v2 | Compute a distance matrix |
| EHC | Ensemble hierarchical clustering via graph partitioning (METIS / MST) |
| embedding_plot | Two-dimensional cluster visualisation (PCA / UMAP / t-SNE) |
| EnsembleClustering | Ensemble clustering via graph partitioning (CSPA / HGPA / MCLA) |
| EvidenceAccumulation | Evidence accumulation clustering (co-association) |
| f.clustABC.MultiSource | Consensus clustering from stacked ABC label matrices |
| FeatSelection | Determine the characteristic features of a cluster or selection |
| FeaturesOfCluster | List all features present in a selected cluster of objects |
| FindCluster | Find a selection of objects in the output of 'ReorderToReference' |
| FindElement | Find an element in a data structure |
| FindGenes | Find the genes shared across methods |
| Geneset.intersect | Intersection over resulting gene sets of 'PathwaysIter' function |
| Geneset.intersectSelection | Intersection over resulting gene sets of 'PathwaysIter' function for a selection of objects |
| HBGF | Hybrid Bipartite Graph Formulation |
| HeatmapPlot | A heatmap of the comparison of two clustering results. |
| HeatmapSelection | A function to select a group of objects via the similarity heatmap. |
| HierarchicalEnsembleClustering | Hierarchical ensemble clustering |
| intNMF | Integrative NMF clustering (intNMF) |
| LabelCols | Helper that colours specific dendrogram leaves |
| LabelPlot | Coloring specific leaves of a dendrogram |
| LinkBasedClustering | Link-based cluster ensembles |
| LUCID | LUCID: latent unknown clustering integrating omics with an outcome |
| mosaic_labels | Extract a flat partition from a MosaiClusteR result |
| mosaic_sim | Simulate a multi-source data set with planted clusters |
| mosaic_toy | Toy multi-omics example data |
| M_ABCdeep | Multi-source M-ABC with a deep-learning (autoencoder) Step 4 (M-ABCdeep) |
| M_ABCdist | Multi-source M-ABC with distance accumulation |
| M_ABCdist.WC | Multi-source M-ABC fused with WeightedClust |
| M_ABCpp | Multi-source Aggregating Bundles of Clusters (M-ABC), C++-accelerated |
| NEMO | NEMO: neighborhood-based multi-omics clustering |
| Normalization | Normalisation of features |
| nugget_cluster | Data-nugget clustering |
| nugget_feature_weights | Feature weights derived from data nuggets |
| PathwayAnalysis | Pathway analysis with intersection over iterations |
| Pathways | Pathway analysis for multiple clustering results |
| PathwaysIter | Iterations of the pathway analysis |
| PathwaysSelection | Pathway analysis for a selection of objects |
| PlotPathways | A GO plot of a pathway analysis output. |
| plot_cluster_profile | Plot one external variable by cluster |
| PreparePathway | Prepare data for pathway analysis |
| ProfilePlot | Plotting gene profiles |
| ReorderToReference | Relabel and reorder clusterings to a reference |
| SelectnrClusters | Select the number of clusters via silhouette widths |
| SharedComps | Objects shared across clusterings |
| SharedGenesPathsFeat | Shared genes, pathways and features across methods |
| SharedSelection | Intersection of genes and pathways over multiple methods for a selection of objects. |
| SharedSelectionLimma | Intersection of genes over multiple methods for a selection of objects. |
| SharedSelectionMLP | Intersection of pathways over multiple methods for a selection of objects. |
| SimilarityHeatmap | A heatmap of similarity values between objects |
| SimilarityMeasure | Similarity of a set of clusterings to a reference |
| simulate_weighting_regime | Simulate data for evaluating feature-weighting schemes (variance vs CV) |
| SNF | Similarity network fusion |
| spectral_clustering | Spectral clustering of an affinity matrix |
| TrackCluster | Track a cluster or a selection of objects across multiple methods |
| WeightedClust | Weighted clustering |
| Whclust | Weighted hierarchical clustering (weighted Ward) |
| Wkmeans | Weighted k-means (minimises WWCSS) |
| WonM | Weighting on Membership clustering |