Alan Murphy, Brian Schilder and Nathan Skene 2021-09-02
The MungeSumstats package is designed to facilitate the standardisation of GWAS summary statistics as utilised in our Nature Genetics paper.1 If you use MungeSumstats, please cite our preprint Murphy and Skene. MungeSumstats: A Bioconductor package for the standardisation and quality control of many GWAS summary statistics.
The package is designed to handle the lack of standardisation of output files by the GWAS community. There is a group who have now manually standardised many GWAS: R interface to the IEU GWAS database API • ieugwasr and gwasvcf but because a lot of GWAS remain closed access, these repositories are not all encompassing.
MungeSumstats provides a framework to standardise the format for any GWAS summary statistics, including those in VCF format, enabling downstream integration and analysis. The package works by addressing the most common discrepancies across summary statistic files. MungeSumstats also offers a range of adjustable, Quality Control (QC).
MungeSumstats is avaiable on Bioconductor (v3.13). To install MungeSumstats on Bioconductor run:
if (!require("BiocManager"))
install.packages("BiocManager")
BiocManager::install("MungeSumstats")
You can then load the package and data package:
library(MungeSumstats)Note that for a number of the checks implored by MungeSumstats a
reference genome is used. If your GWAS summary statistics file of
interest relates to GRCh38, you will need to install
SNPlocs.Hsapiens.dbSNP144.GRCh38 and BSgenome.Hsapiens.NCBI.GRCh38
from Bioconductor as follows:
BiocManager::install("SNPlocs.Hsapiens.dbSNP144.GRCh38")
BiocManager::install("BSgenome.Hsapiens.NCBI.GRCh38")
If your GWAS summary statistics file of interest relates to GRCh37,
you will need to install SNPlocs.Hsapiens.dbSNP144.GRCh37 and
BSgenome.Hsapiens.1000genomes.hs37d5 from Bioconductor as follows:
BiocManager::install("SNPlocs.Hsapiens.dbSNP144.GRCh37")
BiocManager::install("BSgenome.Hsapiens.1000genomes.hs37d5")
These may take some time to install and are not included in the package as some users may only need one of GRCh37/GRCh38. If you are unsure of the genome build, MungeSumstats can also infer this information from your data.
See the Getting started vignette website for up-to-date instructions on usage.
See the OpenGWAS vignette website for information on how to use MungeSumstats to access, standardise and perform quality control on GWAS Summary Statistics from the MRC IEU Open GWAS Project.
If you have any problems please do file an issue here on github.
If you use the MungeSumstats package then please cite
The MungeSumstats package aims to be able to handle the most common summary statistic file formats including VCF. If your file can not be formatted by MungeSumstats feel free to report the bug on github: https://github.com/neurogenomics/MungeSumstats along with your summary statistic file header.
We also encourage people to edit the code to resolve their particular issues too and are happy to incorporate these through pull requests on github. If your summary statistic file headers are not recognised by MungeSumstats but correspond to one of
SNP, BP, CHR, A1, A2, P, Z, OR, BETA, LOG_ODDS, SIGNED_SUMSTAT, N, N_CAS, N_CON,
NSTUDY, INFO or FRQ,
feel free to update the MungeSumstats::sumstatsColHeaders following
the approach in the data.R file and add your mapping. Then use a pull
request on github and we will incorporate this change into the package.
1. Nathan G. Skene, T. E. B., Julien Bryois. Genetic identification of brain cell types underlying schizophrenia. Nature Genetics (2018). doi:10.1038/s41588-018-0129-5