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

The OpenGWAS database comprises over 50,000 curated, QC'd and harmonised complete GWAS summary datasets and can be queried using an API. See here 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:

install.packages("ieugwasr")

or install the developer version of ieugwasr from either our MRCIEU r-universe or from the GitHub repository with, either:

install.packages('ieugwasr', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org'))

or,

remotes::install_github("mrcieu/ieugwasr")

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