- recipe phigaro
Phigaro is a scalable command-line tool for predicting phages and prophages.
- Homepage:
- Documentation:
- License:
MIT / MIT
- Recipe:
Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets.
- package phigaro¶
- Versions:
2.4.0-0,2.3.0-1,2.3.0-0,2.2.6-0- Depends:
on beautifulsoup4
>=4.4.0on biopython
on bs4
on future
on hmmer
on lxml
on numpy
on pandas
>=0.23.4on plotly
on prodigal
on python
>=3.6,<=3.11.7on pyyaml
>=5.1on sh
on six
>=1.7.0
- 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 phigaro
to add into an existing workspace instead, run:
pixi add phigaro
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 phigaro
Alternatively, to install into a new environment, run:
conda create -n envname phigaro
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/phigaro:<tag>
(see phigaro/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/phigaro/README.html)
