Clustering Algorithms for Bioconductor


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Documentation for package ‘bluster’ version 1.16.0

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.defaultScalarArguments Define the default arguments
.defaultScalarArguments-method Agglomerative nesting
.defaultScalarArguments-method Clustering Large Applications
.defaultScalarArguments-method Divisive analysis clustering
.defaultScalarArguments-method Hierarchical clustering
.defaultScalarArguments-method The HierarchicalParam class
.defaultScalarArguments-method Partitioning around medoids
.defaultScalarArguments-method Define the default arguments
.extractScalarArguments Define the default arguments
.showScalarArguments Define the default arguments
AffinityParam Affinity propogation
AffinityParam-class Affinity propogation
AgnesParam Agglomerative nesting
AgnesParam-class Agglomerative nesting
approxSilhouette Approximate silhouette width
BlusterParam-class The BlusterParam class
bootstrapStability Assess cluster stability by bootstrapping
centers The FixedNumberParam class
centers-method The FixedNumberParam class
centers<- The FixedNumberParam class
centers<--method The FixedNumberParam class
ClaraParam Clustering Large Applications
ClaraParam-class Clustering Large Applications
clusterRMSD Compute the RMSD per cluster
clusterRows Cluster rows of a matrix
clusterRows-method Affinity propogation
clusterRows-method Agglomerative nesting
clusterRows-method Clustering Large Applications
clusterRows-method Density-based clustering with DBSCAN
clusterRows-method Divisive analysis clustering
clusterRows-method Dirichlet multinomial mixture clustering
clusterRows-method Hierarchical clustering
clusterRows-method K-means clustering
clusterRows-method Mini-batch k-means clustering
clusterRows-method Graph-based clustering
clusterRows-method Partitioning around medoids
clusterRows-method Clustering with self-organizing maps
clusterRows-method Two step clustering with vector quantization
clusterSweep Clustering parameter sweeps
compareClusterings Compare pairs of clusterings
DbscanParam Density-based clustering with DBSCAN
DbscanParam-class Density-based clustering with DBSCAN
DianaParam Divisive analysis clustering
DianaParam-class Divisive analysis clustering
DmmParam Dirichlet multinomial mixture clustering
DmmParam-class Dirichlet multinomial mixture clustering
FixedNumberParam-class The FixedNumberParam class
HclustParam Hierarchical clustering
HclustParam-class Hierarchical clustering
HierarchicalParam-class The HierarchicalParam class
KmeansParam K-means clustering
KmeansParam-class K-means clustering
KNNGraphParam Graph-based clustering
KNNGraphParam-class Graph-based clustering
linkClusters Create a graph between different clusterings
linkClustersMatrix Create a graph between different clusterings
makeKNNGraph Build a nearest-neighbor graph
makeSNNGraph Build a nearest-neighbor graph
MbkmeansParam Mini-batch k-means clustering
MbkmeansParam-class Mini-batch k-means clustering
mergeCommunities Merge communities from graph-based clustering
neighborPurity Compute neighborhood purity
neighborsToKNNGraph Build a nearest-neighbor graph
neighborsToSNNGraph Build a nearest-neighbor graph
nestedClusters Map nested clusterings
NNGraphParam Graph-based clustering
NNGraphParam-class Graph-based clustering
pairwiseModularity Compute pairwise modularity
pairwiseRand Compute pairwise Rand indices
PamParam Partitioning around medoids
PamParam-class Partitioning around medoids
show-method Affinity propogation
show-method Agglomerative nesting
show-method The BlusterParam class
show-method Clustering Large Applications
show-method Density-based clustering with DBSCAN
show-method Divisive analysis clustering
show-method Dirichlet multinomial mixture clustering
show-method The FixedNumberParam class
show-method Hierarchical clustering
show-method The HierarchicalParam class
show-method K-means clustering
show-method Mini-batch k-means clustering
show-method Graph-based clustering
show-method Partitioning around medoids
show-method Clustering with self-organizing maps
show-method Two step clustering with vector quantization
SNNGraphParam Graph-based clustering
SNNGraphParam-class Graph-based clustering
SomParam Clustering with self-organizing maps
SomParam-class Clustering with self-organizing maps
TwoStepParam Two step clustering with vector quantization
TwoStepParam-class Two step clustering with vector quantization
updateObject-method Hierarchical clustering
updateObject-method K-means clustering
[[-method The BlusterParam class
[[-method Hierarchical clustering
[[<--method The BlusterParam class