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README.md
# AlphaMissense Data for *R* / *Bioconductor* <!-- badges: start --> <!-- badges: end --> The AlphaMissense [publication][Science] outlines how a variant of AlphaFold / DeepMind was used to predict missense variant pathogenicity. Supporting data on [Zenodo][] include, for instance 70+M variants across hg19 and hg38 genome builds. The AlphaMissense package allows ready access to the data, downloading individual files to DuckDB databases for ready exploration and integration into *R* and *Bioconductor* worksflows. [Science]: https://www.science.org/doi/epdf/10.1126/science.adg7492 [Zenodo]: https://zenodo.org//record/8360242 ## Installation Install the package from Bioconductor or GitHub, ensuring correct *Bioconductor* dependencies. When the package is available on *Bioconductor*, use ``` r if (!"BiocManager" %in% rownames(installed.packages())) install.packages("BiocManager", repos = "https://cloud.R-project.org") if (BiocManager::version() >= "3.19") { BiocManager::install("AlphaMissenseR") } else { stop( "'AlphaMissenseR' requires Bioconductor version 3.19 or later, ", "install from GitHub?" ) } ``` Use the pre-release or devel version with ``` r if (!"remotes" %in% rownames(installed.packages())) install.packages("remotes", repos = "https://cloud.R-project.org") remotes::install_github( "mtmorgan/AlphaMissenseR", repos = BiocManager::repositories() ) ``` Load the library. ``` r library(AlphaMissenseR) ``` ## Next steps - Visit the [Introduction][intro] to learn more about accessing AlphaMissense data in *R*. - The [AlphaFold Integration][alphafold] article shows how missense effects can be plotted on AlphaFold (or other) protein structures. - Use [ClinVar Integration][clinvar] to compare AlphaMissense and ClinVar predictions. - Troubleshoot common problems with [Issues & Solutions][issues]. [intro]: ./articles/introduction.html [alphafold]: ./articles/alphafold.html [clinvar]: ./articles/clinvar.html [issues]: ./articles/issues.html