https://github.com/MRCIEU/ieugwasr

R interface to the IEU GWAS database API
https://github.com/MRCIEU/ieugwasr

Last synced: about 2 months ago
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R interface to the IEU GWAS database API

• Host: GitHub
• URL: https://github.com/MRCIEU/ieugwasr
• Owner: MRCIEU
• License: other
• Created: 2019-10-11T13:50:01.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-08-22T13:42:23.000Z (5 months ago)
• Last Synced: 2024-11-28T15:42:07.133Z (about 2 months ago)
• Language: R
• Homepage: https://mrcieu.github.io/ieugwasr/
• Size: 22.7 MB
• Stars: 78
• Watchers: 8
• Forks: 23
• Open Issues: 48
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-complex-trait-genetics - ieugwasr

README

        
# Perform fast queries in R against a massive database of complete GWAS summary data

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The [OpenGWAS database](https://gwas.mrcieu.ac.uk/) comprises over 50,000 curated, QC'd and harmonised complete GWAS summary datasets and can be queried using an API. See [here](https://api.opengwas.io/api/) for documentation on the API itself. This R package is a wrapper to make generic calls to the API, plus convenience functions for specific queries. 

Methods currently implemented:

- Get meta data about specific or all studies

- Obtain the top hits (with on the fly clumping as an option) from each of the GWAS datasets. Clumping and significance thresholds can be specified

- Obtain the summary results of specific variants across specific studies. LD-proxy lookups are performed automatically if a specific variant is absent from a study

- Query a genomic region in a GWAS dataset, e.g. for fine mapping or colocalisation analysis

- Perform PheWAS

There are a few convenience functions also:

- Query dbSNP data, allowing conversion between chromosome:position and rsids and getting annotations

- Perform LD clumping using the server, or locally

- Obtain LD matrices for a list of SNPs using the server or locally (e.g. for fine mapping, colocalisation or Mendelian randomization)

See https://github.com/MRCIEU/gwasglue2 for information about how to connect the genotype and LD data to other packages involving colocalisation, finemapping, visualisation and MR.

## Installation

Install from CRAN using:

```r

install.packages("ieugwasr")

```

or install the developer version of ieugwasr with:

``` r

remotes::install_github("mrcieu/ieugwasr")

```

Browse the vignettes etc for information on how to use this package: https://mrcieu.github.io/ieugwasr/