To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://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 (3.4)

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:

## try http:// if https:// URLs are not supported
source("https://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 1.14.0
In Bioconductor since BioC 2.12 (R-3.0) (4 years)
License GPL (>= 2)
Depends R (>= 2.10.0), survival, coin, fpc, clusterRepro, impute, randomForestSRC, sm, sigaR, Biobase
Imports
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SystemRequirements
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URL
Depends On Me
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Build Report  

Package Archives

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

Package Source HCsnip_1.14.0.tar.gz
Windows Binary HCsnip_1.14.0.zip
Mac OS X 10.9 (Mavericks) HCsnip_1.14.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/HCsnip/tree/release-3.4
Package Short Url http://bioconductor.org/packages/HCsnip/
Package Downloads Report Download Stats

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