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Updated: Nov 22, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
GWASinspector: comprehensive quality control of genome-wide association study results
Alireza Ani1,2, Peter J van der Most1, Harold Snieder1
1Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands.
Summary:
Quality control (QC) of genome wide association study (GWAS) result files has become increasingly difficult due to advances in genomic technology. The main challenges include continuous increases in the number of polymorphic genetic variants contained in recent GWASs and reference panels, the rising number of cohorts participating in a GWAS consortium, and inclusion of new variant types. Here, we present GWASinspector, a flexible R package for comprehensive QC of GWAS results. This package is compatible with recent imputation reference panels, handles insertion/deletion and multi-allelic variants, provides extensive QC reports and efficiently processes big data files. Reference panels covering three human genome builds (NCBI36, GRCh37 and GRCh38) are available. GWASinspector has a user friendly design and allows easy set-up of the QC pipeline through a configuration file. In addition to checking and reporting on individual files, it can be used in preparation of a meta-analysis by testing for systemic differences between studies and generating cleaned, harmonized GWAS files. Comparison with existing GWAS QC tools shows that the main advantages of GWASinspector are its ability to more effectively deal with insertion/deletion and multi-allelic variants and its relatively low memory use.
Availability And Implementation:
Our package is available at The Comprehensive R Archive Network (CRAN): https://CRAN.R-project.org/package=GWASinspector. Reference datasets and a detailed tutorial can be found at the package website at http://gwasinspector.com/.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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