recipe r-singlecellnet

SingleCellNet enables the classifcation of single cell RNA-Seq data across species and platforms.

Homepage:

https://github.com/pcahan1/singlecellnet

License:

MIT / MIT

Recipe:

/r-singlecellnet/meta.yaml

Links:

doi: 10.1016/j.cels.2019.06.004

package r-singlecellnet

versions:

0.4.1-5,  0.4.1-4,  0.4.1-3,  0.4.1-2,  0.4.1-1,  0.4.1-0

depends r-base:

>=4.3,<4.4.0a0

depends r-cowplot:

depends r-data.tree:

depends r-desctools:

depends r-dplyr:

depends r-ggplot2:

depends r-hdf5r:

depends r-patchwork:

depends r-pheatmap:

depends r-randomforest:

depends r-rcolorbrewer:

depends r-reshape2:

depends r-tidyr:

depends r-umap:

depends r-viridis:

requirements:

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 r-singlecellnet

and update with::

   mamba update r-singlecellnet

To create a new environment, run:

mamba create --name myenvname r-singlecellnet

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/r-singlecellnet:<tag>

(see `r-singlecellnet/tags`_ for valid values for ``<tag>``)

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