Bioconductor version: Release (2.7)
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 and Greg Wall
Maintainer: Katherine S. Pollard
To install this package, start R and enter:
source("http:///biocLite.R")
biocLite("hopach")
| bootplot.pdf | ||
| dplot.pdf | ||
| R Script | hopach | |
| hopachManuscript.pdf | ||
| MSS.pdf |
| biocViews | Clustering |
| Depends | R, cluster, Biobase, methods |
| Imports | Biobase, cluster, graphics, grDevices, methods, stats, utils |
| Suggests | |
| System Requirements | |
| License | GPL (>= 2) |
| URL | http://www.stat.berkeley.edu/~laan/, http://docpollard.com/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | BiocCaseStudies |
| Version | 2.10.0 |
| Package Source | hopach_2.10.0.tar.gz |
| Windows Binary | hopach_2.10.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | hopach_2.10.0.tgz |
| Package Downloads Report | Download Stats |
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