Package Recipe 'bioconductor-scdataviz'

recipe bioconductor-scdataviz

scDataviz: single cell dataviz and downstream analyses

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/scDataviz.html
License:: GPL-3
Recipe:: /bioconductor-scdataviz/meta.yaml

In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a 'plug and play' feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can 'add on' features to these with ease.

package bioconductor-scdataviz¶

Versions:

1.20.0-0, 1.16.0-0, 1.12.0-0, 1.10.0-0, 1.8.0-0, 1.4.0-0, 1.2.0-0, 1.0.0-1, 1.0.0-0

Depends:

on bioconductor-flowcore >=2.22.0,<2.23.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on r-base >=4.5,<4.6.0a0
on r-corrplot
on r-ggplot2
on r-ggrepel
on r-mass
on r-matrixstats
on r-rcolorbrewer
on r-reshape2
on r-scales
on r-seurat
on r-umap

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-scdataviz

to add into an existing workspace instead, run:

pixi add bioconductor-scdataviz

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-scdataviz

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-scdataviz

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-scdataviz:<tag>

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