Protocol for detecting causal variants by co-localizing GWAS and QTL studies using colocRedRibbon.

Theodora Papadopoulou, Aristeidis Sionakidis, Anthony Piron, Miriam Cnop

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Article in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Theodora PapadopoulouULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium; Interuniversity Institute of Bioinformatics in Brussels (IB2), 1050 Brussels, Belgium. Electronic address: theodora.papadopoulou@ulb.be.

Aristeidis SionakidisPrecision Breast Cancer Institute, Department of Oncology, University of Cambridge, Cambridge CB2 0QQ, UK.

Anthony PironInteruniversity Institute of Bioinformatics in Brussels (IB2), 1050 Brussels, Belgium; Pharmacognosy, Bioanalysis and Drug Discovery, Pharmacy Faculty, Université Libre de Bruxelles, 1050 Brussels, Belgium. Electronic address: anthony.piron@ulb.be.

Miriam CnopULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium; Department of Endocrinology, ULB Erasmus Hospital, Brussels University Hospital, Université Libre de Bruxelles, 1070 Brussels, Belgium; WEL Research Institute, 1300 Wavre, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BioinformaticsGenomicsHealth SciencesHigh Throughput Screening

Identifiers

PMID42497061

DOI10.1016/j.xpro.2026.104737

PMCPMC13427430

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