recipe scop3p

The official Scop3P REST API Python client

Homepage:

https://iomics.ugent.be/scop3p/

Documentation:

https://iomics.ugent.be/scop3p/documentation

Developer docs:

https://github.com/Bio2Byte/scop3p-api-client

License:

Apache-2.0

Recipe:

/scop3p/meta.yaml

Links:

doi: 10.5281/zenodo.18909477, doi: 10.1021/acs.jproteome.0c00306

Scop3P provides a unique and powerful resource to explore and understand the impact of phospho-sites on human protein structure and function, and can thus serve as a springboard for researchers seeking to analyse and, interpret a given phospho-site or phosphoprotein in a structural, biophysical, and biological context.

package scop3p

(downloads) docker_scop3p

Versions:

1.1.0-0

Depends:
  • on python >=3.6

  • on requests >=2.0

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 scop3p

to add into an existing workspace instead, run:

pixi add scop3p

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 scop3p

Alternatively, to install into a new environment, run:

conda create -n envname scop3p

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/scop3p:<tag>

(see scop3p/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.

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