- recipe metacerberus
Versatile Functional Ontology Assignments for Metagenomes via Hidden Markov Model (HMM) searching with environmental focus of shotgun meta'omics data
- Homepage:
- License:
BSD / BSD-3-Clause
- Recipe:
- package metacerberus¶
- Versions:
1.4.0-1,1.4.0-0,1.3.1-0,1.3.0-1,1.3.0-0,1.2.1-1,1.2.1-0,1.2-0,1.1-1,1.4.0-1,1.4.0-0,1.3.1-0,1.3.0-1,1.3.0-0,1.2.1-1,1.2.1-0,1.2-0,1.1-1,1.1-0,1.0-1,1.0-0,0.2-1,0.2-0,0.1-0- Depends:
on bbmap
on configargparse
on dominate
on fastp
on fastqc
on flash2
on hydrampp
on metaomestats
on pandas
on phanotate
on plotly
on porechop
on psutil
on pyhmmer
0.10.*on pyrodigal
on pyrodigal-gv
on python
>=3.8on python-kaleido
on scikit-learn
on setuptools
<70.0.0on trnascan-se
- 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 metacerberus
to add into an existing workspace instead, run:
pixi add metacerberus
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 metacerberus
Alternatively, to install into a new environment, run:
conda create -n envname metacerberus
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/metacerberus:<tag>
(see metacerberus/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:
[](http://bioconda.github.io/recipes/metacerberus/README.html)
