Clustering Algorithms for Bioconductor

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Documentation for package ‘bluster’ version 1.12.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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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