- recipe sadie-antibody
The Complete Antibody Library
- Homepage:
- Developer docs:
- License:
MIT
- Recipe:
SADIE (Sequencing Analysis and Data library for Immunoinformatics Exploration) provides command-line apps and a Python API for antibody/AIRR analyses.
- package sadie-antibody¶
-
- Versions:
2.0.0-0- Depends:
on biopython
>=1.84on click
>=8.0,<8.2on filetype
>=1.2.0on ipython
>=8.18.0on openpyxl
>=3.1.0on pandas
>=2.3,<3on pip
on pyarrow
>=20.0.0on pydantic
>=2.0.0,<3.0.0on pyhmmer
>=0.11.1on python
>=3.9,<3.14on python-levenshtein
>=0.27.0on pyyaml
>=6.0on requests
>=2.32.0on rich
>=14.1.0on scikit-learn
>=1.5.0on scipy
>=1.11.0on semantic_version
on yarl
>=1.9.0
- 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 sadie-antibody
to add into an existing workspace instead, run:
pixi add sadie-antibody
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 sadie-antibody
Alternatively, to install into a new environment, run:
conda create -n envname sadie-antibody
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/sadie-antibody:<tag>
(see sadie-antibody/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/sadie-antibody/README.html)