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Updated: Aug 6, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Protocol for detecting causal variants by co-localizing GWAS and QTL studies using colocRedRibbon
Theodora Papadopoulou1, Aristeidis Sionakidis2, Anthony Piron3
1ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium; Interuniversity Institute of Bioinformatics in Brussels (IB2), 1050 Brussels, Belgium.
Abstract:
Here, we present a protocol for using colocRedRibbon to link disease-associated variants to gene expression variation by co-localizing genome-wide association study (GWAS) SNPs with cis-expression quantitative trait loci (eQTLs). We describe steps for shortlisting GWAS and eQTL variants, computing co-localization statistics, and assessing posterior probabilities. Co-localized variants provide insights into disease mechanisms and potential therapeutic targets. Beyond GWAS-eQTL integration, the protocol can be applied to co-localization analyses across different QTL types and distinct GWAS datasets. For complete details on the use and execution of this protocol, please refer to Piron et al.1.
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