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:

1.16.0-0,  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 bioconductor-flowcore:

>=2.18.0,<2.19.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends bioconductor-singlecellexperiment:

>=1.28.0,<1.29.0

depends r-base:

>=4.4,<4.5.0a0

depends r-corrplot:

depends r-ggplot2:

depends r-ggrepel:

depends r-mass:

depends r-matrixstats:

depends r-rcolorbrewer:

depends r-reshape2:

depends r-scales:

depends r-seurat:

depends r-umap:

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-scdataviz

and update with::

   mamba update bioconductor-scdataviz

To create a new environment, run:

mamba create --name myenvname bioconductor-scdataviz

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-scdataviz:<tag>

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

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