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• W4311474966 abstract "Genetic colocalization is an approach for determining whether a genetic variant at a particular locus is shared across multiple phenotypes. Genome-wide association studies (GWAS) have successfully mapped genetic variants associated with thousands of complex traits and diseases. However, a large proportion of GWAS signals fall in non-coding regions of the genome, making functional interpretation a challenge. Colocalization relies on a Bayesian framework that can integrate summary statistics, for example those derived from GWAS and expression quantitative trait loci (eQTL) mapping, to assess whether two or more independent association signals at a region of interest are consistent with a shared causal variant. The results from a colocalization analysis may be used to evaluate putative causal relationships between omics-based molecular measurements and a complex disease, and can generate hypotheses that may be followed up by tailored experiments. In this article, we present an easy and straightforward protocol for conducting a Bayesian test for colocalization of two traits using the 'coloc' package in R with summary-level results derived from GWAS and eQTL studies. We also provide general guidelines that can assist in the interpretation of findings generated from colocalization analyses. © 2022 Wiley Periodicals LLC. Basic Protocol: Performing a genetic colocalization analysis using the 'coloc' package in R and summary-level data Support Protocol: Installing the 'coloc' R package." @default.
• W4311474966 created "2022-12-26" @default.
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• W4311474966 date "2022-12-01" @default.
• W4311474966 modified "2023-10-11" @default.
• W4311474966 title "Bayesian Genetic Colocalization Test of Two Traits Using <i>coloc</i>" @default.
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• W4311474966 doi "https://doi.org/10.1002/cpz1.627" @default.
• W4311474966 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36515558" @default.
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