recipe deepbinner

A signal-level demultiplexer for Oxford Nanopore reads.

Homepage:

https://github.com/rrwick/Deepbinner

License:

GPL3

Recipe:

/deepbinner/meta.yaml

package deepbinner

versions:

0.2.0-1,  0.2.0-0,  0.1.2-0

depends h5py:

depends keras:

depends matplotlib:

depends noise:

depends numpy:

depends python:

>3

depends tensorflow:

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 deepbinner

and update with::

   mamba update deepbinner

To create a new environment, run:

mamba create --name myenvname deepbinner

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/deepbinner:<tag>

(see `deepbinner/tags`_ for valid values for ``<tag>``)

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