recipe bioconductor-pi

Leveraging Genetic Evidence to Prioritise Drug Targets at the Gene and Pathway Level






Priority index or Pi is developed as a genomic-led target prioritisation system. It integrates functional genomic predictors, knowledge of network connectivity and immune ontologies to prioritise potential drug targets at the gene and pathway level.

package bioconductor-pi

(downloads) docker_bioconductor-pi



depends bioconductor-biocgenerics:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-suprahex:


depends r-base:


depends r-caret:

depends r-dnet:

depends r-dplyr:

depends r-ggnetwork:

depends r-ggplot2:

depends r-ggrepel:

depends r-glmnet:

depends r-igraph:

depends r-lattice:

depends r-mass:

depends r-matrix:

depends r-osfr:

depends r-plot3d:

depends r-purrr:

depends r-randomforest:

depends r-rcircos:

depends r-readr:

depends r-rocr:

depends r-scales:

depends r-tibble:

depends r-tidyr:



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-pi

and update with::

   mamba update bioconductor-pi

To create a new environment, run:

mamba create --name myenvname bioconductor-pi

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

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