To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("BHC")

In most cases, you don't need to download the package archive at all.

BHC

 

   

Bayesian Hierarchical Clustering

Bioconductor version: Release (3.4)

The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. This avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric. This implementation accepts multinomial (i.e. discrete, with 2+ categories) or time-series data. This version also includes a randomised algorithm which is more efficient for larger data sets.

Author: Rich Savage, Emma Cooke, Robert Darkins, Yang Xu

Maintainer: Rich Savage <r.s.savage at warwick.ac.uk>

Citation (from within R, enter citation("BHC")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("BHC")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("BHC")

 

PDF R Script Bayesian Hierarchical Clustering
PDF   Reference Manual

Details

biocViews Clustering, Microarray, Software
Version 1.26.0
In Bioconductor since BioC 2.7 (R-2.12) (6.5 years)
License GPL-3
Depends
Imports
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Depends On Me
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Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source BHC_1.26.0.tar.gz
Windows Binary BHC_1.26.0.zip (32- & 64-bit)
Mac OS X 10.9 (Mavericks) BHC_1.26.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/BHC/tree/release-3.4
Package Short Url http://bioconductor.org/packages/BHC/
Package Downloads Report Download Stats

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