To install this package, start R and enter:

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

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

RCASPAR

   

This package is for version 2.10 of Bioconductor; for the stable, up-to-date release version, see RCASPAR.

A package for survival time prediction based on a piecewise baseline hazard Cox regression model.

Bioconductor version: 2.10

The package is the R-version of the C-based software \bold{CASPAR} (Kaderali,2006: \url{http://bioinformatics.oxfordjournals.org/content/22/12/1495}). It is meant to help predict survival times in the presence of high-dimensional explanatory covariates. The model is a piecewise baseline hazard Cox regression model with an Lq-norm based prior that selects for the most important regression coefficients, and in turn the most relevant covariates for survival analysis. It was primarily tried on gene expression and aCGH data, but can be used on any other type of high-dimensional data and in disciplines other than biology and medicine. biocViews: aCGH, GeneExpression, Genetics, Proteomics, Visualization

Author: Douaa Mugahid

Maintainer: Douaa Mugahid <douaa.mugahid at gmail.com>, Lars Kaderali <lars.kaderali at bioquant.uni-heidelberg.de>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("RCASPAR")

 

PDF RCASPAR: Software for high-dimentional-data driven survival time prediction
PDF   Reference Manual

Details

biocViews Software
Version 1.2.0
In Bioconductor since BioC 2.9 (R-2.14) (4.5 years)
License GPL (>=3)
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Package Archives

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

Package Source RCASPAR_1.2.0.tar.gz
Windows Binary RCASPAR_1.2.0.zip
Mac OS X 10.6 (Snow Leopard)
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/RCASPAR/tree/release-2.10
Package Short Url http://bioconductor.org/packages/RCASPAR/
Package Downloads Report Download Stats

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