recipe bioconductor-rtnsurvival

Survival analysis using transcriptional networks inferred by the RTN package






RTNsurvival is a tool for integrating regulons generated by the RTN package with survival information. For a given regulon, the 2-tailed GSEA approach computes a differential Enrichment Score (dES) for each individual sample, and the dES distribution of all samples is then used to assess the survival statistics for the cohort. There are two main survival analysis workflows: a Cox Proportional Hazards approach used to model regulons as predictors of survival time, and a Kaplan-Meier analysis assessing the stratification of a cohort based on the regulon activity. All plots can be fine-tuned to the user's specifications.

package bioconductor-rtnsurvival

(downloads) docker_bioconductor-rtnsurvival



depends bioconductor-rtn:


depends bioconductor-rtnduals:


depends r-base:


depends r-data.table:

depends r-dunn.test:

depends r-egg:

depends r-ggplot2:

depends r-pheatmap:

depends r-rcolorbrewer:

depends r-scales:

depends r-survival:



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-rtnsurvival

and update with::

   mamba update bioconductor-rtnsurvival

To create a new environment, run:

mamba create --name myenvname bioconductor-rtnsurvival

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<tag>

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

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