recipe bioconductor-phenotest

Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation.



GPL (>=2)



Tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided.

package bioconductor-phenotest

(downloads) docker_bioconductor-phenotest



depends bioconductor-annotate:


depends bioconductor-annotationdbi:


depends bioconductor-biobase:


depends bioconductor-biomart:


depends bioconductor-category:


depends bioconductor-genefilter:


depends bioconductor-gseabase:


depends bioconductor-heatplus:


depends bioconductor-hgu133a.db:


depends bioconductor-hopach:


depends bioconductor-limma:


depends r-base:


depends r-bma:

depends r-ellipse:

depends r-ggplot2:

depends r-gplots:

depends r-hmisc:

depends r-mgcv:

depends r-survival:

depends r-xtable:



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-phenotest

and update with::

   mamba update bioconductor-phenotest

To create a new environment, run:

mamba create --name myenvname bioconductor-phenotest

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-phenotest/tags`_ for valid values for ``<tag>``)

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