The MungeSumstats
package is designed to facilitate the
standardisation of GWAS summary statistics as utilised in our Nature
Genetics paper.1
The package is designed to handle the lack of standardisation of output
files by the GWAS community. The MRC IEU Open
GWAS team have provided full summary
statistics for >10k GWAS, which are API-accessible via the
ieugwasr
and
gwasvcf
packages. But these GWAS
are only standardised in the sense that they are VCF format, and can be
fully standardised with MungeSumstats
.
MungeSumstats
provides a framework to standardise the format for any
GWAS summary statistics, including those in VCF format, enabling
downstream integration and analysis. It addresses the most common
discrepancies across summary statistic files, and offers a range of
adjustable Quality Control (QC) steps.
If you use MungeSumstats
, please cite the original authors of the GWAS
as well as:
Alan E Murphy, Brian M Schilder, Nathan G Skene (2021) MungeSumstats: A Bioconductor package for the standardisation and quality control of many GWAS summary statistics. Bioinformatics, btab665, https://doi.org/10.1093/bioinformatics/btab665
MungeSumstats
is available 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.
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
Issue on GitHub
along with your summary statistics 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 data("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.
We would like to acknowledge all those who have contributed to
MungeSumstats
development:
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