/gwasvcf

Reading, querying and writing GWAS summary data in VCF format

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Reading, querying and writing GWAS summary data in VCF format

Lifecycle: experimental codecov R-CMD-check

Complete GWAS summary datasets are now abundant. A large repository of curated, harmonised and QC'd datasets is available in the IEU GWAS database. They can be queried via the API directly, or through the ieugwasr R package, or the ieugwaspy python package. However, for faster querying that can be used in a HPC environment, accessing the data directly and not through cloud systems is advantageous.

We developed a format for storing and harmonising GWAS summary data known as GWAS VCF format which can be created using gwas2vcf. All the data in the IEU GWAS database is available for download in this format. This R package provides fast and convenient functions for querying and creating GWAS summary data in GWAS VCF format (v1.0). See also pygwasvcf a Python3 parser for querying GWAS VCF files.

This package includes:

  • a wrapper around the bioconductor/VariantAnnotation package, providing functions tailored to GWAS VCF for reading, querying, creating and writing GWAS VCF format files
  • some LD related functions such as using a reference panel to extract proxies, create LD matrices and perform LD clumping
  • functions for harmonising a dataset against the reference genome and creating GWAS VCF files.

See also the gwasglue R package for methods to connect the VCF data to Mendelian randomization, colocalisation, fine mapping etc.

Installation

remotes::install_github("mrcieu/gwasvcf")

Usage

See vignettes here: https://mrcieu.github.io/gwasvcf.

Citation

If using GWAS-VCF files please reference the studies that you use and the following paper:

The variant call format provides efficient and robust storage of GWAS summary statistics. Matthew Lyon, Shea J Andrews, Ben Elsworth, Tom R Gaunt, Gibran Hemani, Edoardo Marcora. bioRxiv 2020.05.29.115824; doi: https://doi.org/10.1101/2020.05.29.115824

Reference datasets

Example GWAS VCF (GIANT 2010 BMI):

1000 genomes reference panels for LD for each superpopulation - used by default in OpenGWAS:

RSID index for faster querying:

1000 genomes annotations in vcf format harmonised against human genome reference:

Notes

Example data

data.vcf.gz and data.vcf.gz.tbi are the first few rows of the Speliotes 2010 BMI GWAS

The eur.bed/bim/fam files are the same range as data.vcf.gz, from here http://fileserve.mrcieu.ac.uk/ld/data_maf0.01_rs_ref.tgz