- recipe janusx
GWAS and genomic selection toolkit with Rust-accelerated kernels.
- Homepage:
- Documentation:
- License:
AGPL-3.0-or-later
- Recipe:
- Links:
JanusX is a high-performance toolkit for genome-wide association studies (GWAS), genomic selection (GS), and post-analysis visualization.
This Bioconda recipe packages the Python+Rust core and provides the `jxpy` command entrypoint. Launcher-specific features (`jx`, self-update/runtime management, `fastq2vcf`, and `fastq2count`) are intentionally excluded from this package scope.
- package janusx¶
- Versions:
1.0.20-0- Depends:
on __osx
>=11.0on joblib
>=1.5on matplotlib-base
on numpy
>=1.21,<3on pandas
<3.0on psutil
on python
>=3.10,<3.11.0a0on python_abi
3.10.* *_cp310on rich
on rich-argparse
on scikit-learn
on scipy
on statsmodels
on tqdm
on xgboost
- Additional platforms:
linux-aarch64,osx-arm64
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 janusx
to add into an existing workspace instead, run:
pixi add janusx
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 janusx
Alternatively, to install into a new environment, run:
conda create -n envname janusx
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/janusx:<tag>
(see janusx/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/janusx/README.html)
