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

Bioconductor version: Release (2.11)

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.

Author: Douaa Mugahid

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

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


biocViews GeneExpression, Genetics, Proteomics, Software, Visualization, aCGH
Version 1.4.0
In Bioconductor since BioC 2.9 (R-2.14)
License GPL (>=3)
System Requirements
Depends On Me
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Package Source RCASPAR_1.4.0.tar.gz
Windows Binary RCASPAR_1.4.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) RCASPAR_1.4.0.tgz
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