Abstract
MotivationGenome‐wide association studies (GWAS) summary statistics have popularized and accelerated genetic research. However, a lack of standardization of the file formats used has proven problematic when running secondary analysis tools or performing meta-analysis studies.ResultsTo address this issue, we have developed MungeSumstats, a Bioconductor R package for the standardization and quality control of GWAS summary statistics. MungeSumstats can handle the most common summary statistic formats, including variant call format (VCF) producing a reformatted, standardized, tabular summary statistic file, VCF or R native data object.Availability and implementationMungeSumstats is available on Bioconductor (v 3.13) and can also be found on Github at: https://neurogenomics.github.io/MungeSumstats.Supplementary informationSupplementary data are available at Bioinformatics online.
Highlights
Genome-wide association studies (GWAS) summary statistics are used to distribute the most important outputs of GWASs in a manner which does not require the transfer of individual-level personally identifiable information from participants
Summary statistics from past studies tend to become more valuable over time as it becomes possible to meta-analyze and integrate them with new annotation information through approaches such as Linkage Disequilibrium Score Regression (LDSC) (Bulik-Sullivan et al, 2015), Generalized Gene-Set Analysis of GWAS Data, MAGMA and multi-phenotype investigations (Aguirre et al, 2021; Tanigawa et al, 2019)
The variant call format to store GWAS summary statistics (GWAS-VCF) (Lyon et al, 2021) has been developed which has manually converted over 10 000 GWAS to this format
Summary
Genome-wide association studies (GWAS) summary statistics are used to distribute the most important outputs of GWASs in a manner which does not require the transfer of individual-level personally identifiable information from participants. The standardization of GWAS summary statistics requires quality control to ensure cohesive integration.
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