Package Recipe 'bioconductor-proteingymr'

recipe bioconductor-proteingymr

Programmatic access to ProteinGym datasets in R/Bioconductor

Homepage:: https://bioconductor.org/packages/3.20/data/experiment/html/ProteinGymR.html
License:: Artistic-2.0
Recipe:: /bioconductor-proteingymr/meta.yaml

The ProteinGymR package provides analysis-ready data resources from ProteinGym, generated by Notin et al., 2023. ProteinGym comprises a collection of benchmarks for evaluating the performance of models predicting the effect of point mutations. This package provides access to 1. Deep mutational scanning (DMS) scores from 217 assays measuring the impact of all possible amino acid substitutions across 186 proteins, 2. AlphaMissense pathogenicity scores for ~1.6 M substitutions in the ProteinGym DMS data, and 3. five performance metrics for 62 variant prediction models in a zero-shot setting.

package bioconductor-proteingymr¶

Versions:

1.4.0-0

Depends:

on bioconductor-annotationhub >=4.0.0,<4.1.0
on bioconductor-data-packages >=20260207
on bioconductor-experimenthub >=3.0.0,<3.1.0
on curl
on r-base >=4.5,<4.6.0a0
on r-dplyr
on r-htmltools
on r-lifecycle
on r-purrr
on r-queryup
on r-rlang
on r-spdl
on r-stringr
on r-tidyr
on r-tidyselect

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 bioconductor-proteingymr

to add into an existing workspace instead, run:

pixi add bioconductor-proteingymr

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 bioconductor-proteingymr

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-proteingymr

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/bioconductor-proteingymr:<tag>

(see bioconductor-proteingymr/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/bioconductor-proteingymr/README.html)