Package Recipe 'fpocketr'

recipe fpocketr

CLI tool to find, characterize, and visualize RNA-ligand binding pockets.

Homepage:: https://github.com/Weeks-UNC/fpocketR
License:: MIT
Recipe:: /fpocketr/meta.yaml
Links:: doi: 10.1101/2025.03.13.643147

fpocketR is an RNA-specific wrapper for fpocket 4.0, providing CLI tools to find, characterize, and visualize RNA binding pockets for drug-like ligands. Only available for x86_64 architectures on linux and MacOS.

package fpocketr¶

Versions:

1.3.4-0

Depends:

on biopython 1.83
on fpocket 4.0.3.*
on pandas
on prody 2.3.0
on pymol-open-source 2.5
on python >=3.11,<3.12
on rdkit 2023.9.6
on scipy 1.12.0
on seaborn
on trimesh 4.2.0

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 fpocketr

to add into an existing workspace instead, run:

pixi add fpocketr

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 fpocketr

Alternatively, to install into a new environment, run:

conda create -n envname fpocketr

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/fpocketr:<tag>

(see fpocketr/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:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/fpocketr/README.html)