Package Recipe 'bioconductor-enrichedheatmap'

recipe bioconductor-enrichedheatmap

Making Enriched Heatmaps

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/EnrichedHeatmap.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-enrichedheatmap/meta.yaml

Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. Here we implement enriched heatmap by ComplexHeatmap package. Since this type of heatmap is just a normal heatmap but with some special settings, with the functionality of ComplexHeatmap, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondance between different data sources.

package bioconductor-enrichedheatmap¶

Versions:

1.40.1-0, 1.36.0-0, 1.32.0-0, 1.30.0-0, 1.27.2-1, 1.27.2-0, 1.24.0-2, 1.24.0-1, 1.24.0-0,

1.40.1-0, 1.36.0-0, 1.32.0-0, 1.30.0-0, 1.27.2-1, 1.27.2-0, 1.24.0-2, 1.24.0-1, 1.24.0-0, 1.22.0-0, 1.20.0-1, 1.20.0-0, 1.18.2-0, 1.16.0-0, 1.14.0-1, 1.12.0-0

Depends:

on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-complexheatmap >=2.26.1,<2.27.0a0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.1,<1.63.0a0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-iranges >=2.44.0,<2.45.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-circlize >=0.4.5
on r-getoptlong
on r-locfit
on r-matrixstats
on r-rcpp

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-enrichedheatmap

to add into an existing workspace instead, run:

pixi add bioconductor-enrichedheatmap

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-enrichedheatmap

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-enrichedheatmap

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-enrichedheatmap:<tag>

(see bioconductor-enrichedheatmap/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-enrichedheatmap/README.html)