To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("RCASPAR")
In most cases, you don't need to download the package archive at all.
Bioconductor version: 2.14
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>
Citation (from within R,
enter citation("RCASPAR")
):
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("RCASPAR")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RCASPAR")
R Script | RCASPAR: Software for high-dimentional-data driven survival time prediction | |
Reference Manual |
biocViews | GeneExpression, Genetics, Proteomics, Software, Visualization, aCGH |
Version | 1.10.0 |
In Bioconductor since | BioC 2.9 (R-2.14) |
License | GPL (>=3) |
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Follow Installation instructions to use this package in your R session.
Package Source | RCASPAR_1.10.0.tar.gz |
Windows Binary | RCASPAR_1.10.0.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | RCASPAR_1.10.0.tgz |
Mac OS X 10.9 (Mavericks) | RCASPAR_1.10.0.tgz |
Browse/checkout source | (username/password: readonly) |
Package Downloads Report | Download Stats |
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