recipe selene-sdk

Framework for developing sequence-level deep learning networks.

Homepage:

https://github.com/FunctionLab/selene

License:

BSD 3-clause clear

Recipe:

/selene-sdk/meta.yaml

package selene-sdk

(downloads) docker_selene-sdk

versions:
0.6.0-00.5.3-10.5.3-00.5.0-50.5.0-40.5.0-30.5.0-10.5.0-00.4.8-3

0.6.0-00.5.3-10.5.3-00.5.0-50.5.0-40.5.0-30.5.0-10.5.0-00.4.8-30.4.8-20.4.8-10.4.8-00.4.7-00.4.6-00.4.5-00.4.4-00.4.3-00.4.2-00.4.1-00.3.0-20.3.0-10.3.0-00.2.0-10.2.0-00.1.3-00.1.2-00.0.1-0

depends click:

depends h5py:

depends libgcc:

>=13

depends matplotlib-base:

>=2.2.3

depends numpy:

>=1.24.4,<2.0a0

depends pandas:

depends plotly:

depends pyfaidx:

depends pytabix:

depends python:

>=3.8,<3.9.0a0

depends python_abi:

3.8.* *_cp38

depends pytorch:

>=1.0.0,<=2.3.1

depends pyyaml:

>=5.1

depends ruamel.yaml:

depends scikit-learn:

depends scipy:

depends seaborn:

depends statsmodels:

requirements:

additional platforms:
linux-aarch64

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 selene-sdk

and update with::

   mamba update selene-sdk

To create a new environment, run:

mamba create --name myenvname selene-sdk

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/selene-sdk:<tag>

(see `selene-sdk/tags`_ for valid values for ``<tag>``)

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