- recipe alleleflux
A tool for fine-grained evolutionary analysis of microbial populations and communities
- Homepage:
- Documentation:
- License:
GPL3 / GPL-3.0-or-later
- Recipe:
AlleleFlux is a python package for analyzing allele frequencies trajectories in metagenomic data. It profiles MAG (Metagenome-Assembled Genome) populations across samples, detecting parallel evolution through allele frequency changes.
- package alleleflux¶
- Versions:
0.1.14-0,0.1.4-0- Depends:
on biopython
on click
on intervaltree
on matplotlib-base
on numpy
on pandas
on pysam
on python
>=3.9on pyyaml
on questionary
on r-base
on r-tidyr
on rpy2
on scipy
on seaborn
on snakemake-executor-plugin-cluster-generic
on snakemake-minimal
>=8.0.0on statsmodels
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 alleleflux
to add into an existing workspace instead, run:
pixi add alleleflux
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 alleleflux
Alternatively, to install into a new environment, run:
conda create -n envname alleleflux
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/alleleflux:<tag>
(see alleleflux/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/alleleflux/README.html)
