This is the development version of ProteinGymR; for the stable release version, see ProteinGymR.
Programmatic access to ProteinGym datasets in R/BioconductorBioconductor version: Development (3.22)
The ProteinGymR package provides analysis-ready data resources from ProteinGym, generated by Notin et al., 2023, as well as built-in functionality to visualize the data. 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. model performance metrics and prediction scores from 79 variant prediction models in the zero-shot setting and 12 models in the semi-supervised setting.
Author: Tram Nguyen [aut, cre] ORCID: 0000-0003-4809-6227 , Pascal Notin [aut], Aaron Kollasch [aut], Debora Marks [aut], Ludwig Geistlinger [aut]
Maintainer: Tram Nguyen <Tram_Nguyen at hms.harvard.edu>
Citation (from within R, entercitation("ProteinGymR")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("ProteinGymR")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("ProteinGymR")Follow Installation instructions to use this package in your R session.
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