recipe bioconductor-s4vectors

Foundation of vector-like and list-like containers in Bioconductor







biotools: s4vectors, doi: 10.1038/nmeth.3252

The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, Factor, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).

package bioconductor-s4vectors

(downloads) docker_bioconductor-s4vectors



depends bioconductor-biocgenerics:


depends libblas:


depends libgcc-ng:


depends liblapack:


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-s4vectors

and update with::

   mamba update bioconductor-s4vectors

To create a new environment, run:

mamba create --name myenvname bioconductor-s4vectors

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-s4vectors/tags`_ for valid values for ``<tag>``)

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