recipe r-scbio

Cellular population mapping (CPM) a deconvolution algorithm in which single-cell genomics is required in only one or a few samples, where in other samples of the same tissue, only bulk genomics is measured and the underlying fine resolution cellular heterogeneity is inferred.

Homepage:

https://github.com/amitfrish/scBio

License:

GPL / GPL-2

Recipe:

/r-scbio/meta.yaml

Links:

doi: 10.1038/s41592-019-0355-5

package r-scbio

(downloads) docker_r-scbio

versions:

0.1.4-3,  0.1.4-2,  0.1.4-1,  0.1.4-0

depends bioconductor-limma:

depends r-base:

>=4.4,<4.5.0a0

depends r-dosnow:

depends r-fields:

depends r-foreach:

depends r-liblinear:

depends r-raster:

depends r-sp:

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 r-scbio

and update with::

   mamba update r-scbio

To create a new environment, run:

mamba create --name myenvname r-scbio

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-scbio:<tag>

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

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