Man pages for MosaiClusteR
An Umbrella Framework for Multi-Source and Multi-Omics Clustering

ABCdeep.SingleInMultipleSingle-source ABC with a deep-learning (autoencoder) Step 4...
ABCdist.SingleInMultipleSingle-source ABC with distance accumulation
ABCpp.SingleInMultipleSingle-source Aggregating Bundles of Clusters (ABC),...
ADCAggregated data clustering
ADECAggregated data ensemble clustering
BinFeaturesPlot_MultipleDataVisualization of characteristic binary features of multiple...
BinFeaturesPlot_SingleDataVisualization of characteristic binary features of a single...
BoxPlotDistanceBox plots of one distance matrix categorized against another...
CECComplementary ensemble clustering
CharacteristicFeaturesDetermine the characteristic features of clusters
characterize_clustersCharacterise clusters with external (biological / clinical)...
ChooseClusterInteractive plot to determine DE Genes and DE features for a...
ClusterSingle-source base clustering
cluster_agreementAgreement between two partitions
cluster_biology_panelPanel of cluster characterisation plots
ClusterColsHelper that colours dendrogram leaves by cluster membership
ClusteringAggregationClustering aggregation
clustering_concordanceCompare clustering solutions to each other (no ground truth...
cluster_k_sweepShow the clustering at every k (see how it deteriorates)
ClusterPlotColouring clusters in a dendrogram
cluster_selection_plotJustify the number of clusters (silhouette + elbow / scree)
ColorPaletteCreate a color palette to be used in the plots
ColorsNamesFunction that annotates colors to their names
compare_clusteringsCompare two clusterings derived from distance matrices
CompareInteractiveInteractive comparison of single and multiple source...
compare_methods_plotVisually compare clustering solutions with ComparePlot (no...
ComparePlotComparison of clustering results over multiple methods
CompareSilClusterCompares medoid clustering results based on silhouette widths
CompareSvsMComparison of clustering results for the single and multiple...
ConsensusClusteringVoting-based consensus clustering
ContFeaturesPlotPlot of continuous features
create_data_nuggetsCreate data nuggets from a data matrix
CVAACumulative Voting Aggregation (CVAA / W-CVAA)
CyclogramComparison of clustering results over multiple results in...
DetermineWeight_SilClustDetermines an optimal weight for weighted clustering by...
DetermineWeight_SimClustDetermines an optimal weight for weighted clustering by...
DiffGenesFind differentially expressed genes
DiffGenesSelectionDifferential expression for a selection of objects
DistanceCompute a distance matrix
distanceheatmapsDetermine the distance in a heatmap
EHCEnsemble hierarchical clustering via graph partitioning...
embedding_plotTwo-dimensional cluster visualisation (PCA / UMAP / t-SNE)
enriched_featuresTidy CharacteristicFeatures() output for plotting
EnsembleClusteringEnsemble clustering via graph partitioning (CSPA / HGPA /...
EvidenceAccumulationEvidence accumulation clustering (co-association)
f.clustABC.MultiSourceConsensus clustering from stacked ABC label matrices
FeatSelectionDetermine the characteristic features of a cluster or...
FeaturesOfClusterList all features present in a selected cluster of objects
FindClusterFind a selection of objects in the output of...
FindElementFind an element in a data structure
FindGenesFind the genes shared across methods
Geneset.intersectIntersection over resulting gene sets of 'PathwaysIter'...
Geneset.intersectSelectionIntersection over resulting gene sets of 'PathwaysIter'...
HBGFHybrid Bipartite Graph Formulation
HeatmapPlotA heatmap of the comparison of two clustering results.
HeatmapSelectionA function to select a group of objects via the similarity...
HierarchicalEnsembleClusteringHierarchical ensemble clustering
intNMFIntegrative NMF clustering (intNMF)
LabelColsHelper that colours specific dendrogram leaves
LabelPlotColoring specific leaves of a dendrogram
LinkBasedClusteringLink-based cluster ensembles
LUCIDLUCID: latent unknown clustering integrating omics with an...
M_ABCMulti-source Aggregating Bundles of Clusters (M-ABC),...
M_ABCdeepMulti-source M-ABC with a deep-learning (autoencoder) Step 4...
M_ABCdistMulti-source M-ABC with distance accumulation
M_ABCdist.WCMulti-source M-ABC fused with WeightedClust
mosaic_labelsExtract a flat partition from a MosaiClusteR result
MosaiClusteRMosaiClusteR: An Umbrella Framework for Multi-Source and...
mosaic_simSimulate a multi-source data set with planted clusters
mosaic_toyToy multi-omics example data
NEMONEMO: neighborhood-based multi-omics clustering
NormalizationNormalisation of features
nugget_clusterData-nugget clustering
nugget_feature_weightsFeature weights derived from data nuggets
PathwayAnalysisPathway analysis with intersection over iterations
PathwaysPathway analysis for multiple clustering results
PathwaysIterIterations of the pathway analysis
PathwaysSelectionPathway analysis for a selection of objects
plot_cluster_profilePlot one external variable by cluster
plot_pathwaysModern Gene Ontology / pathway-enrichment plots
PlotPathwaysA GO plot of a pathway analysis output.
PreparePathwayPrepare data for pathway analysis
ProfilePlotPlotting gene profiles
ReorderToReferenceRelabel and reorder clusterings to a reference
SelectnrClustersSelect the number of clusters via silhouette widths
SharedCompsObjects shared across clusterings
SharedGenesPathsFeatShared genes, pathways and features across methods
SharedSelectionIntersection of genes and pathways over multiple methods for...
SharedSelectionLimmaIntersection of genes over multiple methods for a selection...
SharedSelectionMLPIntersection of pathways over multiple methods for a...
SimilarityHeatmapA heatmap of similarity values between objects
SimilarityMeasureSimilarity of a set of clusterings to a reference
simulate_weighting_regimeSimulate data for evaluating feature-weighting schemes...
SNFSimilarity network fusion
spectral_clusteringSpectral clustering of an affinity matrix
TrackClusterTrack a cluster or a selection of objects across multiple...
WeightedClustWeighted clustering
WhclustWeighted hierarchical clustering (weighted Ward)
WkmeansWeighted k-means (minimises WWCSS)
WonMWeighting on Membership clustering
MosaiClusteR documentation built on Oct. 25, 2026, 1:08 a.m.