CONQUER: an interactive toolbox to understand functional consequences of GWAS hits

Area of Science:

• Genomics
• Bioinformatics
• Systems Biology

Background:

• Genome-wide association studies (GWAS) identify genetic variants associated with traits.
• Many GWAS risk loci reside in non-coding and intergenic regions, posing challenges for mechanistic interpretation.
• Understanding the functional impact of these loci on gene regulation and pathways is crucial.

Purpose of the Study:

• To develop a user-friendly R-package, CONQUER, for integrative analysis of single nucleotide polymorphisms (SNPs).
• To facilitate the interpretation of genetic risk loci by considering them as interconnected networks rather than isolated factors.
• To provide interactive visualizations of genetic data from multiple repositories.

Main Methods:

• Acquisition of SNP data from static and dynamic repositories (e.g., GTExPortal, Epigenomics Project, 4D genome database).
• Utilized GRCh38/hg38 genome build for data integration.
• Developed interactive visualization tools within the R-package.

Main Results:

• CONQUER enables integrative analysis of multiple SNPs, moving beyond single-locus interpretations.
• The package provides interactive visualizations for immediate data exploration.
• It supports data retrieval from diverse genomic repositories.

Conclusions:

• CONQUER offers a novel approach to understanding the complex genetic architecture of traits.
• The tool aids in deciphering the functional consequences of non-coding genetic variants.
• It promotes a network-based perspective for interpreting genetic risk loci.