recipe metabinner

Ensemble binning method to recover individual genomes from complex microbial communities

Homepage:

https://github.com/ziyewang/MetaBinner

License:

BSD

Recipe:

/metabinner/meta.yaml

package metabinner

(downloads) docker_metabinner

versions:

1.4.4-1,  1.4.4-0,  1.4.3-0,  1.4.2-0

depends biolib:

0.1.6.*

depends biopython:

1.76.*

depends bwa:

0.7.17.*

depends checkm-genome:

1.1.3.*

depends click:

7.1.2.*

depends fraggenescan:

1.31.*

depends hmmer:

3.1b2.*

depends numpy:

1.18.1.*

depends pandas:

1.0.1.*

depends pplacer:

1.1.alpha19.*

depends prodigal:

2.6.3.*

depends python:

3.7.6.*

depends samtools:

1.9.*

depends scikit-learn:

0.22.1.*

depends scipy:

1.4.1.*

requirements:

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 metabinner

and update with::

   mamba update metabinner

To create a new environment, run:

mamba create --name myenvname metabinner

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/metabinner:<tag>

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

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/metabinner/README.html)