recipe bioconductor-rgenometracks

Integerated visualization of epigenomic data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/rGenomeTracks.html

License:

GPL-3

Recipe:

/bioconductor-rgenometracks/meta.yaml

rGenomeTracks package leverages the power of pyGenomeTracks software with the interactivity of R. pyGenomeTracks is a python software that offers robust method for visualizing epigenetic data files like narrowPeak, Hic matrix, TADs and arcs, however though, here is no way currently to use it within R interactive session. rGenomeTracks wrapped the whole functionality of pyGenomeTracks with additional utilites to make to more pleasant for R users.

package bioconductor-rgenometracks

(downloads) docker_bioconductor-rgenometracks

versions:

1.8.0-01.6.0-01.4.0-01.0.0-0

depends bioconductor-rgenometracksdata:

>=0.99.0,<0.100.0

depends r-base:

>=4.3,<4.4.0a0

depends r-imager:

depends r-reticulate:

requirements:

Installation

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-rgenometracks

and update with::

   mamba update bioconductor-rgenometracks

To create a new environment, run:

mamba create --name myenvname bioconductor-rgenometracks

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 quay.io/biocontainers/bioconductor-rgenometracks:<tag>

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

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