recipe bioconductor-gmoviz

Seamless visualization of complex genomic variations in GMOs and edited cell lines

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/gmoviz.html

License:

GPL-3

Recipe:

/bioconductor-gmoviz/meta.yaml

Genetically modified organisms (GMOs) and cell lines are widely used models in all kinds of biological research. As part of characterising these models, DNA sequencing technology and bioinformatics analyses are used systematically to study their genomes. Therefore, large volumes of data are generated and various algorithms are applied to analyse this data, which introduces a challenge on representing all findings in an informative and concise manner. `gmoviz` provides users with an easy way to visualise and facilitate the explanation of complex genomic editing events on a larger, biologically-relevant scale.

package bioconductor-gmoviz

versions:

1.18.0-0,  1.14.0-0,  1.12.0-0,  1.10.0-0,  1.6.0-0,  1.4.0-0,  1.2.0-1,  1.2.0-0,  1.0.0-0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0

depends bioconductor-biostrings:

>=2.74.0,<2.75.0

depends bioconductor-complexheatmap:

>=2.22.0,<2.23.0

depends bioconductor-genomeinfodb:

>=1.42.0,<1.43.0

depends bioconductor-genomicalignments:

>=1.42.0,<1.43.0

depends bioconductor-genomicfeatures:

>=1.58.0,<1.59.0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-iranges:

>=2.40.0,<2.41.0

depends bioconductor-rsamtools:

>=2.22.0,<2.23.0

depends bioconductor-rtracklayer:

>=1.66.0,<1.67.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends r-base:

>=4.4,<4.5.0a0

depends r-circlize:

depends r-colorspace:

depends r-gridbase:

depends r-pracma:

requirements:

additional platforms:

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-gmoviz

and update with::

   mamba update bioconductor-gmoviz

To create a new environment, run:

mamba create --name myenvname bioconductor-gmoviz

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-gmoviz:<tag>

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

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