ProteinGymR
Programmatic access to ProteinGym datasets in R/Bioconductor
Bioconductor version: Release (3.20)
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.
Author: Tram Nguyen [aut, cre] , Pascal Notin [aut], Aaron Kollasch [aut], Debora Marks [aut], Ludwig Geistlinger [aut]
Maintainer: Tram Nguyen <Tram_Nguyen at hms.harvard.edu>
citation("ProteinGymR")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ProteinGymR")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("ProteinGymR")
Data access and visualization | HTML | R Script |
Reference Manual |
Details
biocViews | CellCulture, ExperimentData, ExperimentHub, Homo_sapiens_Data, PackageTypeData, Proteome, ReproducibleResearch, SequencingData |
Version | 1.0.0 |
License | Artistic-2.0 |
Depends | R (>= 4.4.0) |
Imports | ExperimentHub, dplyr, forcats, ggdist, gghalves, ggplot2, purrr, queryup, spdl, tidyr, tidyselect |
System Requirements | |
URL | https://github.com/ccb-hms/ProteinGymR |
Bug Reports | https://github.com/ccb-hms/ProteinGymR/issues |
See More
Suggests | ComplexHeatmap, AnnotationHub, tibble, stringr, BiocStyle, knitr, testthat (>= 3.0.0) |
Linking To | |
Enhances | |
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Imports Me | |
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Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | ProteinGymR_1.0.0.tar.gz |
Windows Binary (x86_64) | |
macOS Binary (x86_64) | |
macOS Binary (arm64) | |
Source Repository | git clone https://git.bioconductor.org/packages/ProteinGymR |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/ProteinGymR |
Package Short Url | https://bioconductor.org/packages/ProteinGymR/ |
Package Downloads Report | Download Stats |