recipe bioconductor-streamer

Enabling stream processing of large files







biotools: streamer, doi: 10.1038/nmeth.3252

Large data files can be difficult to work with in R, where data generally resides in memory. This package encourages a style of programming where data is 'streamed' from disk into R via a `producer' and through a series of `consumers' that, typically reduce the original data to a manageable size. The package provides useful Producer and Consumer stream components for operations such as data input, sampling, indexing, and transformation; see package?Streamer for details.

package bioconductor-streamer

(downloads) docker_bioconductor-streamer



depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends bioconductor-graph:


depends bioconductor-graph:


depends bioconductor-rbgl:


depends bioconductor-rbgl:


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-streamer

and update with::

   mamba update bioconductor-streamer

To create a new environment, run:

mamba create --name myenvname bioconductor-streamer

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

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