recipe bioconductor-genetonic

Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis






This package provides functionality to combine the existing pieces of the transcriptome data and results, making it easier to generate insightful observations and hypothesis. Its usage is made easy with a Shiny application, combining the benefits of interactivity and reproducibility e.g. by capturing the features and gene sets of interest highlighted during the live session, and creating an HTML report as an artifact where text, code, and output coexist. Using the GeneTonicList as a standardized container for all the required components, it is possible to simplify the generation of multiple visualizations and summaries.

package bioconductor-genetonic

(downloads) docker_bioconductor-genetonic



depends bioconductor-annotationdbi:


depends bioconductor-complexheatmap:


depends bioconductor-deseq2:


depends bioconductor-go.db:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-backbone:

depends r-base:


depends r-bs4dash:


depends r-circlize:

depends r-colorspace:

depends r-colourpicker:

depends r-complexupset:

depends r-dendextend:

depends r-dplyr:

depends r-dt:

depends r-dynamictreecut:

depends r-expm:

depends r-ggforce:

depends r-ggplot2:

depends r-ggrepel:

depends r-ggridges:

depends r-igraph:

depends r-matrixstats:

depends r-plotly:

depends r-rcolorbrewer:

depends r-rintrojs:

depends r-rlang:

depends r-rmarkdown:

depends r-scales:

depends r-shiny:

depends r-shinyace:

depends r-shinycssloaders:

depends r-shinywidgets:

depends r-tidyr:

depends r-tippy:

depends r-viridis:

depends r-visnetwork:



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-genetonic

and update with::

   mamba update bioconductor-genetonic

To create a new environment, run:

mamba create --name myenvname bioconductor-genetonic

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

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