recipe deepbgc

DeepBGC - Biosynthetic Gene Cluster detection and classification

Homepage:

https://github.com/Merck/DeepBGC

License:

MIT / MIT

Recipe:

/deepbgc/meta.yaml

package deepbgc

versions:

0.1.31-0,  0.1.30-2,  0.1.30-1,  0.1.30-0,  0.1.29-0,  0.1.28-1,  0.1.28-0,  0.1.27-0,  0.1.26-0, 

0.1.31-0,  0.1.30-2,  0.1.30-1,  0.1.30-0,  0.1.29-0,  0.1.28-1,  0.1.28-0,  0.1.27-0,  0.1.26-0,  0.1.23-0,  0.1.22-0,  0.1.21-0,  0.1.20-0,  0.1.19-0,  0.1.18-1,  0.1.18-0,  0.1.17-0,  0.1.16-0,  0.1.15-0,  0.1.14-0,  0.1.13-0,  0.1.10-0,  0.1.9-0,  0.1.8-0,  0.1.7-0,  0.1.6-0,  0.1.5-0,  0.1.4-0,  0.1.3-1,  0.1.3-0

depends appdirs:

>=1.4.3

depends biopython:

>=1.78

depends hmmer:

>=3.1b2

depends keras:

2.2.4

depends matplotlib-base:

2.2.3

depends numpy:

1.16.1

depends pandas:

0.24.1

depends prodigal:

depends protobuf:

<=3.19.0

depends python:

>=3.5

depends scikit-learn:

0.21.3

depends scipy:

1.2.0

depends tensorflow:

>=1.12.0,<2.0.0

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 deepbgc

and update with::

   mamba update deepbgc

To create a new environment, run:

mamba create --name myenvname deepbgc

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/deepbgc:<tag>

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

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