eaQTLdb

eaQTLdb catalogs genetic variants that influence enhancer activity in cancer by mapping enhancer activity quantitative trait loci (eaQTLs) using enhancer RNA (eRNA) signals to characterize genetic regulation across cancer types.

Key Features:

• Multiomics Data Integration: Systematically identifies and catalogs genetic variants that affect enhancer activity (eaQTLs) using multiomics datasets.
• Cancer Type-Specific Analysis: Profiles the effects of genetic variants on enhancer activity across diverse cancer types.
• Linkage to Cancer Hallmarks and Survival Outcomes: Connects eaQTLs with cancer hallmarks and correlates them with patient overall survival data.
• Immune Cell Infiltration Correlation: Associates eaQTLs with infiltration abundance of 24 immune cell types.
• Colocalization Analyses: Performs colocalization analyses between eaQTLs and GWAS signals across 59 complex diseases and traits.

Scientific Applications:

• Variant and Enhancer Prioritization: Prioritizes candidate genetic variants and enhancers implicated in cancer based on eaQTL evidence.
• Pathway and Tumor Microenvironment Investigation: Enables study of dysregulated pathways and the tumor immune microenvironment by linking eaQTLs to hallmarks and immune infiltration.
• Genetic–Clinical and GWAS Integration: Facilitates linking genetic regulation of enhancers to clinical outcomes and GWAS-identified disease or trait loci.

Methodology:

eaQTLs are identified and cataloged from multiomics datasets using eRNA as an enhancer activity proxy; analyses include correlations with overall survival, associations with infiltration abundance of 24 immune cell types, and colocalization with GWAS signals across 59 complex diseases and traits.