recipe semibin

Metagenomic binning with semi-supervised siamese neural networks

Homepage:

https://github.com/BigDataBiology/SemiBin

Documentation:

https://semibin.readthedocs.io/en/latest/

License:

MIT / MIT

Recipe:

/semibin/meta.yaml

Links:

doi: 10.1038/s41467-022-29843-y, doi: 10.1093/bioinformatics/btad209, biotools: semibin

package semibin

versions:

2.1.0-0,  2.0.2-0,  2.0.1-0,  2.0.0-1,  2.0.0-0,  1.5.1-0,  1.5.0-1,  1.5.0-0,  1.4.0-0, 

2.1.0-0,  2.0.2-0,  2.0.1-0,  2.0.0-1,  2.0.0-0,  1.5.1-0,  1.5.0-1,  1.5.0-0,  1.4.0-0,  1.3.1-0,  1.3.0-0,  1.2.0-0,  1.1.1-1,  1.1.1-0,  1.1.0-0,  1.0.3-0,  1.0.2-0,  1.0.1-0,  1.0.0-0,  0.7.0-0,  0.6.0-0,  0.5.0-1,  0.5.0-0,  0.4.0-0,  0.3-0,  0.2-1,  0.2-0

depends bedtools:

depends coloredlogs:

depends hmmer:

depends mmseqs2:

13.45111.*

depends numexpr:

depends numpy:

depends pandas:

depends prodigal:

depends python:

>=3.7

depends python-igraph:

depends pytorch:

depends pyyaml:

depends requests:

depends samtools:

depends scikit-learn:

depends tqdm:

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 semibin

and update with::

   mamba update semibin

To create a new environment, run:

mamba create --name myenvname semibin

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/semibin:<tag>

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

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