recipe r-loom

An interface for the single-cell RNAseq-oriented loom format. Loom files are an HDF5-based format for storing and interacting with large single-cell RNAseq datasets. loomR provides an interface for working with loom files in a loom-specific way; we provide routines for validating loom files, iterating with chunks through data within the loom file, and provide a platform for other packages to build support for loom files.

Homepage:

https://github.com/mojaveazure/loomR

License:

GPL3 / GPL-3

Recipe:

/r-loom/meta.yaml

package r-loom

(downloads) docker_r-loom

versions:

0.2.0.2-7,  0.2.0.2-6,  0.2.0.2-5,  0.2.0.2-4,  0.2.0.2-3,  0.2.0.2-2,  0.2.0.2-1,  0.2.0.2-0,  0.2.0.1-0

depends icu:

>=64

depends r-base:

>=4.4,<4.5.0a0

depends r-hdf5r:

depends r-iterators:

depends r-itertools:

depends r-matrix:

depends r-pbapply:

depends r-stringr:

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-loom

and update with::

   mamba update r-loom

To create a new environment, run:

mamba create --name myenvname r-loom

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-loom:<tag>

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

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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