recipe bioconductor-rlassocox

A reweighted Lasso-Cox by integrating gene interaction information

Homepage:

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

License:

Artistic-2.0

Recipe:

/bioconductor-rlassocox/meta.yaml

RLassoCox is a package that implements the RLasso-Cox model proposed by Wei Liu. The RLasso-Cox model integrates gene interaction information into the Lasso-Cox model for accurate survival prediction and survival biomarker discovery. It is based on the hypothesis that topologically important genes in the gene interaction network tend to have stable expression changes. The RLasso-Cox model uses random walk to evaluate the topological weight of genes, and then highlights topologically important genes to improve the generalization ability of the Lasso-Cox model. The RLasso-Cox model has the advantage of identifying small gene sets with high prognostic performance on independent datasets, which may play an important role in identifying robust survival biomarkers for various cancer types.

package bioconductor-rlassocox

versions:

1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-0,  1.2.0-0,  1.0.0-0

depends r-base:

>=4.4,<4.5.0a0

depends r-glmnet:

depends r-igraph:

depends r-matrix:

depends r-survival:

requirements:

additional platforms:

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-rlassocox

and update with::

   mamba update bioconductor-rlassocox

To create a new environment, run:

mamba create --name myenvname bioconductor-rlassocox

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-rlassocox:<tag>

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

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