RCASPAR

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

Bioconductor version: 2.9

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>

To install this package, start R and enter:

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

To cite this package in a publication, start R and enter:

    citation("RCASPAR")

Documentation

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

Details

biocViews
Depends
Imports
Suggests
System Requirements
License GPL (>=3)
URL
Depends On Me
Imports Me
Suggests Me
Version 1.0.0
Since Bioconductor 2.9 (R-2.14)

Package Downloads

Package Source RCASPAR_1.0.0.tar.gz
Windows Binary RCASPAR_1.0.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary RCASPAR_1.0.0.tgz
Package Downloads Report Download Stats

Workflows »

Common Bioconductor workflows include:

 

Mailing Lists »

Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!

Fred Hutchinson Cancer Research Center