Project details for APCluster

Screenshot APCluster 1.3.2

by UBod - June 12, 2013, 11:38:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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Affinity propagation (AP) is a clustering algorithm that has been introduced by Brendan J. Frey and Delbert Dueck. The authors themselves describe affinity propagation as follows:

"An algorithm that identifies exemplars among data points and forms clusters of data points around these exemplars. It operates by simultaneously considering all data point as potential exemplars and exchanging messages between data points until a good set of exemplars and clusters emerges."

AP has been applied in various fields recently, among which bioinformatics is becoming increasingly important. Frey and Dueck have made their algorithm available as Matlab code. Matlab, however, is relatively uncommon in bioinformatics. Instead, the statistical computing platform R has become a widely accepted standard in this field. In order to leverage affinity propagation for bioinformatics applications, we have implemented affinity propagation as an R package. Note, however, that the given package is in no way restricted to bioinformatics applications. It is as generally applicable as Frey’s and Dueck’s original Matlab code.

The package further implements leveraged affinity propagation, exemplar-based agglomerative clustering, and various tools for visual analysis of clustering results.

Changes to previous version:
  • plotting of clustering results extended to data sets with more than two dimensions (resulting in the clustering result being superimposed in a scatterplot matrix); the variant that plot() can be used to draw a heatmap has been removed. From now on, heatmap() must always be used.
  • improved NA handling
  • correction of input check in apcluster() and apclusterL() (previously, both functions issued a warning whenever argument p had length > 1)
  • corresponding updates and further improvements of help pages and vignette
BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Platform Independent
Data Formats: Any Format Supported By R
Tags: Clustering, Kernels, Distance Function, Clustering Algorithm, Affinity Propagation, Similarity Measure
Archive: download here


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