Package Recipe 'bioconductor-gmoviz'

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:

1.22.0-0, 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,

1.22.0-0, 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:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-genomicalignments >=1.46.0,<1.47.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-seqinfo >=1.0.0,<1.1.0
on r-base >=4.5,<4.6.0a0
on r-circlize
on r-colorspace
on r-gridbase
on r-pracma

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-gmoviz

to add into an existing workspace instead, run:

pixi add bioconductor-gmoviz

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-gmoviz

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-gmoviz

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-gmoviz:<tag>

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-gmoviz/README.html)