knitr::opts_chunk$set(tidy = FALSE, warning = FALSE, message = FALSE)
r badger::badge_bioc_release(color = "black")
r badger::badge_github_version(color = "black")
r badger::badge_last_commit(branch = "master")
r badger::badge_bioc_download(by = "total", color = "blue")
r badger::badge_license()
r badger::badge_doi(doi = "https://doi.org/10.1093/bioinformatics/btab665", color="blue")
The MungeSumstats
package is designed to facilitate the standardisation of GWAS summary statistics.
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
MungeSumstats
is available on
Bioconductor.
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 there is also a docker image for 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.dbSNP155.GRCh38
and
BSgenome.Hsapiens.NCBI.GRCh38
from Bioconductor as follows:
BiocManager::install("SNPlocs.Hsapiens.dbSNP155.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.dbSNP155.GRCh37
and
BSgenome.Hsapiens.1000genomes.hs37d5
from Bioconductor as follows:
BiocManager::install("SNPlocs.Hsapiens.dbSNP155.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:
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