Package Recipe 'metator'

recipe metator

Metagenomic binning based on Hi-C data.

Homepage:: https://github.com/koszullab/metator
Documentation:: https://github.com/koszullab/metaTOR/blob/v1.3.10/README.md
License:: GPL3 / GPL-3.0-or-later
Recipe:: /metator/meta.yaml
Links:: doi: 10.3389/fgene.2019.00753

package metator¶

Versions:

1.3.10-1, 1.3.10-0, 1.3.7-0

Depends:

on biopython <=1.80
on bowtie2
on bwa
on checkv
on cooler
on hicstuff
on hmmer
on libgcc >=14
on libstdcxx >=14
on looseversion
on micomplete
on networkx
on numpy
on openjdk
on pairix
on pairtools
on pandas
on prodigal
on pyfastx
on pysam
on python >=3.10,<3.11.0a0
on python_abi 3.10.* *_cp310
on samtools
on scikit-learn
on scipy
on seaborn-base

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install metator

to add into an existing workspace instead, run:

pixi add metator

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install metator

Alternatively, to install into a new environment, run:

conda create -n envname metator

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/metator:<tag>

(see metator/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an 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/metator/README.html)