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APCluster - An R Package for Affinity Propagation Clustering

In order to make Affinity Propagation Clustering [Frey & Dueck, 2007] accessible to a wider audience in bioinformatics, we ported the Matlab code published by the authors Frey and Dueck (cf. Affinity Propagation Website) to R.

Installation

The package is available through CRAN - The Comprehensive R Archive Network (click here to view the archive entry of the package). Therefore, the simplest way to install the package is to enter
install.packages("apcluster")
into your R session. If, for what reason ever, you prefer to install the package manually, follow the instructions in the user manual.

The current version of the package is 1.4.7 (released 2018-05-29).

Getting started

  1. To load the package, enter "library(apcluster)" in your R session.
  2. To view the user manual, enter "vignette("apcluster")".
  3. To do a first example, enter "example(apcluster)".

Documentation

  1. User Manual: PDF (1.0MB; last updated on 2018-05-29)
  2. Reference Manual: PDF (254KB; last updated on 2018-05-29; generated automatically from package help pages)

Webinar "Introduction to apcluster"

On June 13, 2013, the maintainer of the package, Ulrich Bodenhofer, gave a webinar on the apcluster package. The webinar was hosted by the Orange County R User Group and moderated by its president, Ray DiGiacomo, Jr. The demo uses Version 1.3.2 of the package (released June 11, 2013).
  1. Complete recording of webinar: YouTube Video (length: 59:17)
  2. Slides of webinar: PDF (6.6MB)
  3. R code used in webinar: R code (4KB)

User support

If you encounter any issues or if you have any question that might be of interest also for other users, before writing a private message to the package developers/maintainers, please consider posting to the R-help Mailing List or on StackOverflow.

Citing this package

If you use this package for research that is published later, you are kindly asked to cite it as follows:

U. Bodenhofer, A. Kothmeier, and S. Hochreiter (2011). APCluster: an R package for affinity propagation clustering. Bioinformatics 27:2463-2464. DOI: 10.1093/bioinformatics/btr406.

Moreover, we insist that, any time you use/cite the package, you also cite the original paper in which affinity propagation has been introduced:

B. J. Frey and D. Dueck (2007). Clustering by passing messages between data points. Science, 315:972-976. DOI: 10.1126/science.1136800.

Change log

Version 1.4.7, released 2018-05-29:
  • correction of aggExCluster() C++ code to avoid compilation error on Solaris
Version 1.4.6, released 2018-05-28:
  • aggExCluster() now implemented in C++ instead of R in order to improve speed
  • further correction of conditional loading of package suggested by vignette
Version 1.4.5, released 2018-01-31:
  • loading of suggested Bioconductor packages now performed conditionally to avoid problems when building the package on some platforms that do not have the Bioconductor packages installed
Version 1.4.4, released 2017-07-01:
  • changed dependency to suggested package 'kebabs' to version of at least 1.5.4 for improved interoperability
  • bug fix in as.dendrogram() method with signature 'AggExResult'
  • added discrepancy metric to distance computations and updated src/distanceL.c to new version
  • registered C/C++ subroutines
  • minor change in the vignette template
  • moved NEWS to inst/NEWS
  • added inst/COPYRIGHT
Version 1.4.3, released 2016-02-24:
  • added optional color legend to heatmap plotting; in line with this change, some minor changes to the interface of the heatmap() function
  • corresponding updates of help pages and vignette
Version 1.4.2, released 2015-12-24:
  • switched sequence kernel example in vignette from 'kernlab' to 'kebabs' package
  • workaround to ensure that all apcluster*() methods are able to process KernelMatrix objects (cf. kebabs package)
  • replaced data set ch22Promoters by plain text file (FASTA format) in inst/examples
  • bug fix in the heatmap() method
  • vignette engine changed from Sweave to knitr
Version 1.4.1, released 2014-12-09:
  • fixes in C++ code of sparse affinity propagation
Version 1.4.0, released 2014-12-01:
  • added apcluster() method for sparse similarity matrices; as a consequence, the package now imports the Matrix package and is now also able to handle non-sparse matrix classes defined by the Matrix package. Moreover, similarity functions supplied to the apcluster() method may now also return any matrix type defined by the Matrix package.
  • fix of apcluster() for dense matrices to better support -Inf similarities
  • added apclusterK() method for sparse similarity matrices
  • preferenceRange() is now an S4 generic; re-implementation in C++ to speed up function; changed handling of -Inf similarities for consistency with sparse version
  • added preferenceRange() methods for sparse matrices and dense matrix objects from the Matrix package
  • new conversion methods implemented for converting dense similarity matrices to sparse ones and vice versa; consequently, sparseToFull() is marked as deprecated.
  • adaptation of heatmap() function for improved handling of -Inf similarities
  • adaptations of signatures of '[' and '[[' accessor methods
  • renamed help page of methods for computing similarity matrices to 'similarities' in order to avoid confusion with the accessor method similarity()
  • corresponding updates of help pages and vignette
Version 1.3.5, released 2014-06-26:
  • memory access fixes in C++ code called from apclusterL()
  • minor updates of vignette
Version 1.3.4, released 2013-06-25:
  • added sort() function to rearrange clusters according to sort criterion; note that this is an S3 method (see help page for explanation)
  • improvements and bug fixes of apclusterL() method for signature 'matrix,missing'
  • performance optimizations of apcluster() and apclusterL()
  • plotting of clustering results superimposed in scatter plot matrices now also works for AggExResult objects
  • improvements of consistency of error and warning messages
  • according adaptations of documentation and vignette
  • adapted dependency and linking to Rcpp version 0.11.1 (to avoid issues on Mac OS)
  • minor correction of package namespace
Version 1.3.3, released 2014-02-21:
  • adapted dependencies and linking to Rcpp version 0.11.0
  • cleared up package dependencies
Version 1.3.2, released 2013-06-11:
  • 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
Version 1.3.1,, released 2013-04-22:
  • re-implementation of heatmap() method: dendrograms can now be plotted even for APResult and ExClust objects as well as for cluster hierarchies based on prior clusterings; color bars can now be switched off and colors can be changed by user (by new sideColor argument); dendrograms can be switched on and off (by Rowv and Colv arguments);
  • added as.hclust() and as.dendrogram() methods
  • added new arguments base, showSamples, and horiz to the plot() method
  • with signature (x="AggExResult", y="missing"); moreover, parameters for changing the appearance of the height axis are now respected as well
  • streamlining of methods (redundant definition of inherited methods removed)
  • various minor improvements of code and documentation
Version 1.3.0, released 2013-01-07:
  • added Leveraged Affinity Propagation Clustering
  • re-implementation of main functions as S4 generic methods in order to facilitate the convenient internal computation of similarity matrices
  • for convenience, similarity matrices can be stored as part of clustering results
  • heatmap plotting now done by heatmap() which has been defined as S4 generic
  • extended interface to functions for computing similarity matrices
  • added function corSimMat()
  • implementation of length() method for classes APResult, AggExResult, and ExClust
  • added accessor function to extract clustering levels from AggExResult objects
  • correction of exemplars returned by apcluster() for details=TRUE in slot idxAll of returned APResult object
  • when using data stored in a data frame, now categorical columns are explicitly omitted, thereby, avoiding warnings
  • plotting of clustering results along with original data (2D only) has been accelerated
  • all clustering methods now store their calls into the result objects
  • updates and extensions of help pages and vignette
Version 1.2.1, released 2012-06-12:
  • added convenient accessor functions to extracting cluster indices from APResult and ExClust objects
  • added a function for coercing an APResult object into an ExClust object
  • correction of color bar on the left side of heatmaps (default behavior of RowSideColors parameter changed with R 2.15)
Version 1.2.0, released 2012-03-26:
  • reimplementation of apcluster() in C++ using the Rcpp package which reduces computation times by a factor of 9-10
  • obsolete function apclusterLM() removed
  • updates of help pages and vignette
Version 1.1.1, released 2011-09-08:
  • updated citation
  • minor corrections in help pages and vignette
Version 1.1.0, released 2011-06-15:
  • exemplar-based agglomerative clustering (function aggExCluster()) added
  • added various plotting functions, e.g. for dendrograms and heatmaps
  • added sequence analysis example to vignette
  • extension of vignette according to new functionality
  • re-organization of variable names in vignette
  • added option 'verbose' to apclusterK()
  • numerous minor corrections in help pages and vignette
Version 1.0.3, released 2011-03-01:
  • Makefile in inst/doc eliminated to avoid installation problems
  • renamed vignette to "apcluster"
Version 1.0.2, released 2010-03-19:
  • replacement of computation of responsibilities and availabilities in apcluster() by pure matrix operations; traditional implementation according to Frey and Dueck still available as function apclusterLM();
  • improved support for named objects
  • new function for computing label vectors
  • re-organization of package source files and help pages
Version 1.0.1, released 2010-03-02:
first public release

Contact

For suggestions, bug reports, and other matters regarding the package, please contact [email protected].