# 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