recipe bioconductor-gdsarray

Representing GDS files as array-like objects






GDS files are widely used to represent genotyping or sequence data. The GDSArray package implements the `GDSArray` class to represent nodes in GDS files in a matrix-like representation that allows easy manipulation (e.g., subsetting, mathematical transformation) in _R_. The data remains on disk until needed, so that very large files can be processed.

package bioconductor-gdsarray

(downloads) docker_bioconductor-gdsarray



depends bioconductor-biocgenerics:


depends bioconductor-delayedarray:


depends bioconductor-gdsfmt:


depends bioconductor-s4vectors:


depends bioconductor-seqarray:


depends bioconductor-snprelate:


depends r-base:




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-gdsarray

and update with::

   mamba update bioconductor-gdsarray

To create a new environment, run:

mamba create --name myenvname bioconductor-gdsarray

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<tag>

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

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