To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("HCsnip")

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

HCsnip

Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree

Bioconductor version: Release (2.14)

Decompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy.

Author: Askar Obulkasim

Maintainer: Askar Obulkasim <askar703 at gmail.com>

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

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("HCsnip")

Documentation

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

browseVignettes("HCsnip")

 

PDF R Script HCsnip
PDF   Reference Manual

Details

biocViews Clustering, GeneExpression, Microarray, Software, aCGH
Version 1.4.0
In Bioconductor since BioC 2.12 (R-3.0)
License GPL (>= 2)
Depends R (>= 2.10.0), survival, coin, fpc, clusterRepro, impute, randomForestSRC, sm, sigaR, Biobase
Imports
Suggests
System Requirements
URL
Depends On Me
Imports Me
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Package Archives

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

Package Source HCsnip_1.4.0.tar.gz
Windows Binary HCsnip_1.4.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) HCsnip_1.4.0.tgz
Mac OS X 10.9 (Mavericks) HCsnip_1.4.0.tgz
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