Protocol demonstrates co-localization of disease variants with gene expression in various QTL types, suggesting insights for therapy.
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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Papadopoulou et al. (2026) studied this question.
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