recipe bioconductor-ggbio

Visualization tools for genomic data







biotools: ggbio

The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

package bioconductor-ggbio

(downloads) docker_bioconductor-ggbio



depends bioconductor-annotationdbi:


depends bioconductor-annotationfilter:


depends bioconductor-biobase:


depends bioconductor-biocgenerics:


depends bioconductor-biostrings:


depends bioconductor-biovizbase:


depends bioconductor-bsgenome:


depends bioconductor-ensembldb:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicfeatures:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-organismdbi:


depends bioconductor-rsamtools:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends bioconductor-variantannotation:


depends r-base:


depends r-ggally:

depends r-ggplot2:


depends r-gridextra:

depends r-gtable:

depends r-hmisc:

depends r-reshape2:

depends r-rlang:

depends r-scales:



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-ggbio

and update with::

   mamba update bioconductor-ggbio

To create a new environment, run:

mamba create --name myenvname bioconductor-ggbio

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

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