- recipe pgap2
PGAP2: a comprehensive pan-genome analysis pipeline for prokaryotic genomes.
- Homepage:
- License:
MIT / MIT
- Recipe:
- package pgap2¶
-
- Versions:
2.0-0,1.1.0-0,1.0.9-0,1.0.8-0,1.0.6-0,1.0.4-0,1.0.3-0- Depends:
on bcbio-gff
0.7.1on biopython
1.82on blast
on cd-hit
on clipkit
on clonalframeml
on diamond
on ete3
3.1.3on fasttree
on htslib
on iqtree
on loguru
0.6.0on mafft
on mcl
on minifasta
3.0.2on miniprot
on mmseqs2
on muscle
on networkx
3.3on numpy
1.23.3on pandas
1.5.0on perl-bio-tools-run-alignment-tcoffee
on prodigal
on pyecharts
2.0.8on pyfastani
0.5.1on python
>=3.10on python-edlib
1.3.9on r-base
on r-dplyr
on r-fastbaps
on r-ggpubr
on r-ggrepel
on r-optparse
on r-patchwork
on r-tidyr
on raxml-ng
on scikit-learn
1.1.2on scipy
1.9.1on seqtk
on svgwrite
on tajimas_d
2.0.2on tqdm
4.64.1
- 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 pgap2
to add into an existing workspace instead, run:
pixi add pgap2
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 pgap2
Alternatively, to install into a new environment, run:
conda create -n envname pgap2
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/pgap2:<tag>
(see pgap2/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/pgap2/README.html)