recipe bioconductor-rcaspar

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

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/RCASPAR.html

License:

GPL (>=3)

Recipe:

/bioconductor-rcaspar/meta.yaml

Links:

biotools: rcaspar, doi: 10.1038/nmeth.3252

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.

package bioconductor-rcaspar

(downloads) docker_bioconductor-rcaspar

versions:
1.48.0-0,  1.46.0-0,  1.44.0-0,  1.40.0-0,  1.38.0-0,  1.36.0-1,  1.36.0-0,  1.34.0-0,  1.32.0-0, 

1.48.0-0,  1.46.0-0,  1.44.0-0,  1.40.0-0,  1.38.0-0,  1.36.0-1,  1.36.0-0,  1.34.0-0,  1.32.0-0,  1.30.0-1,  1.30.0-0,  1.28.0-0,  1.26.0-0,  1.24.0-0,  1.22.0-0

depends r-base:

>=4.3,<4.4.0a0

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-rcaspar

and update with::

   mamba update bioconductor-rcaspar

To create a new environment, run:

mamba create --name myenvname bioconductor-rcaspar

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/bioconductor-rcaspar:<tag>

(see `bioconductor-rcaspar/tags`_ for valid values for ``<tag>``)

Download stats

Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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