- recipe bioconductor-rcaspar
A package for survival time prediction based on a piecewise baseline hazard Cox regression model.
- Homepage:
https://bioconductor.org/packages/3.20/bioc/html/RCASPAR.html
- License:
GPL (>=3)
- Recipe:
- 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¶
- Versions:
1.56.0-0,1.52.0-0,1.48.0-0,1.46.0-0,1.44.0-0,1.40.0-0,1.38.0-0,1.36.0-1,1.36.0-0,1.56.0-0,1.52.0-0,1.48.0-0,1.46.0-0,1.44.0-0,1.40.0-0,1.38.0-0,1.36.0-1,1.36.0-0,1.34.0-0,1.32.0-0,1.30.0-1,1.30.0-0,1.28.0-0,1.26.0-0,1.24.0-0,1.22.0-0- Depends:
on r-base
>=4.5,<4.6.0a0
- Additional platforms:
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install bioconductor-rcaspar
to add into an existing workspace instead, run:
pixi add bioconductor-rcaspar
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install bioconductor-rcaspar
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-rcaspar
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/bioconductor-rcaspar:<tag>
(see bioconductor-rcaspar/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-rcaspar/README.html)
