Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)

Bioconductor version: 2.9

The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).

Author: Katherine S. Pollard, with Mark J. van der Laan <laan at stat.berkeley.edu> and Greg Wall

Maintainer: Katherine S. Pollard <katherine.pollard at gladstone.ucsf.edu>

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PDF bootplot.pdf
PDF dplot.pdf
PDF R Script hopach
PDF hopachManuscript.pdf
PDF   Reference Manual


biocViews Clustering
Depends R (>= 2.11.0), cluster, Biobase, methods
Imports Biobase, cluster, graphics, grDevices, methods, stats, utils
System Requirements
License GPL (>= 2)
URL http://www.stat.berkeley.edu/~laan/, http://docpollard.org/
Depends On Me
Imports Me phenoTest
Suggests Me BiocCaseStudies
Version 2.14.0
Since Bioconductor 1.6 (R-2.1) or earlier

Package Downloads

Package Source hopach_2.14.0.tar.gz
Windows Binary hopach_2.14.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary hopach_2.14.0.tgz
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