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

Area of Science:

• Genetics
• Genomics
• Bioinformatics

Background:

• Genome-wide association studies (GWAS) identify genetic variants associated with diseases.
• Expression quantitative trait loci (eQTLs) link genetic variants to gene expression levels.
• Integrating GWAS and eQTL data is crucial for understanding disease mechanisms.

Purpose of the Study:

• To present a protocol for co-localizing GWAS SNPs with cis-eQTLs using colocRedRibbon.
• To link disease-associated variants to gene expression variation.
• To identify potential therapeutic targets by understanding genetic contributions to disease.

Main Methods:

• Developing a protocol for variant analysis using colocRedRibbon.
• Shortlisting relevant GWAS and eQTL variants.
• Computing co-localization statistics and assessing posterior probabilities.

Main Results:

• The protocol enables the co-localization of GWAS SNPs and cis-eQTLs.
• Co-localized variants offer insights into disease-associated genetic factors.
• The method facilitates the identification of potential therapeutic targets.

Conclusions:

• The presented protocol provides a robust method for integrating GWAS and eQTL data.
• This approach enhances the understanding of genetic underpinnings of diseases.
• The protocol is adaptable for various quantitative trait loci (QTL) types and GWAS datasets.