recipe sanntis

SMBGC Annotation using Neural Networks Trained on Interpro Signatures.

Homepage:

https://github.com/Finn-Lab/SanntiS

License:

Apache / Apache-2.0

Recipe:

/sanntis/meta.yaml

package sanntis

versions:

0.9.4.1-0,  0.9.4.0-0,  0.9.3.5-1,  0.9.3.5-0,  0.9.3.4-0,  0.9.3.3-0,  0.9.3.2-0,  0.9.3.1-0,  0.9.3-0, 

0.9.4.1-0,  0.9.4.0-0,  0.9.3.5-1,  0.9.3.5-0,  0.9.3.4-0,  0.9.3.3-0,  0.9.3.2-0,  0.9.3.1-0,  0.9.3-0,  0.9.1-0,  0.1.0-0

depends biopython:

depends hmmer:

depends joblib:

>=1.0.1

depends numpy:

>=1.16,<1.20

depends openjdk:

>=11.0

depends perl:

>=5

depends prodigal:

depends python:

>=3.9

depends scikit-learn:

0.24.*

depends scipy:

>=1.7.3,<1.8.0

depends tensorflow:

2.4.*

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 sanntis

and update with::

   mamba update sanntis

To create a new environment, run:

mamba create --name myenvname sanntis

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/sanntis:<tag>

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

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Render an badge with the following MarkDown:

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