- recipe semibin
Metagenomic binning with siamese neural networks
- Homepage:
- Documentation:
- License:
MIT / MIT
- Recipe:
- Links:
doi: 10.1038/s41467-022-29843-y, doi: 10.1093/bioinformatics/btad209, biotools: semibin
- package semibin¶
- Versions:
2.2.1-0,2.2.0-1,2.2.0-0,2.1.0-0,2.0.2-0,2.0.1-0,2.0.0-1,2.0.0-0,1.5.1-0,2.2.1-0,2.2.0-1,2.2.0-0,2.1.0-0,2.0.2-0,2.0.1-0,2.0.0-1,2.0.0-0,1.5.1-0,1.5.0-1,1.5.0-0,1.4.0-0,1.3.1-0,1.3.0-0,1.2.0-0,1.1.1-1,1.1.1-0,1.1.0-0,1.0.3-0,1.0.2-0,1.0.1-0,1.0.0-0,0.7.0-0,0.6.0-0,0.5.0-1,0.5.0-0,0.4.0-0,0.3-0,0.2-1,0.2-0- Depends:
on bedtools
on coloredlogs
on hmmer
on numexpr
on numpy
on pandas
on prodigal
on python
>=3.7on python-igraph
on pytorch
on pyyaml
on requests
on safetensors
on samtools
on scikit-learn
on tqdm
- 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 semibin
to add into an existing workspace instead, run:
pixi add semibin
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 semibin
Alternatively, to install into a new environment, run:
conda create -n envname semibin
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/semibin:<tag>
(see semibin/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/semibin/README.html)
