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APCluster - An R Package for Affinity Propagation Clustering

Implements Affinity Propagation clustering introduced by Frey and Dueck (2007; DOI:10.1126/science.1136800). The algorithms are largely analogous to the 'Matlab' code published by Frey and Dueck. The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.

This is the source code repository. The package can be installed from CRAN. Further information and installation instructions are also available from http://www.bioinf.jku.at/software/apcluster/.

The package is maintained by Ulrich Bodenhofer. The package itself has grown over the years in which multiple students have contributed significant parts: Johannes Palme, Chrats Melkonian, Andreas Kothmeier, and Nikola Kostic

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Install

install.packages('apcluster')

Monthly Downloads

2,922

Version

1.4.11

License

GPL (>= 2)

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Last Published

September 19th, 2023

Functions in apcluster (1.4.11)

AggExResult-class

Class "AggExResult"
apclusterL

Leveraged Affinity Propagation
apclusterDemo

Affinity Propagation Demo
APResult-class

Class "APResult"
coerce-methods

Coercion of cluster hierarchies
aggExCluster

Exemplar-based Agglomerative Clustering
apcluster

Affinity Propagation
apclusterK

Affinity Propagation for Pre-defined Number of Clusters
apcluster-package

APCluster Package
ExClust-class

Class "ExClust"
plot

Plot Clustering Results
sort-methods

Sort clusters
conversions

Conversions Between Dense and Sparse Similarity Matrices
show-methods

Display Clustering Result Objects
cutree-methods

Cut Out Clustering Level from Cluster Hierarchy
preferenceRange

Determine Meaningful Ranges for Input Preferences
similarities

Methods for Computing Similarity Matrices
heatmap

Plot Heatmap
labels-methods

Generate label vector from clustering result