Qtlizer

QTLizer: QTL-Based Annotation of GWAS Variants

QTLizer annotates genome-wide association study (GWAS) variants by integrating quantitative trait loci (QTL) data to resolve variant-to-gene relationships and functional effects on gene expression and protein abundance.

Key Features:

• QTL Database Integration: Integrates published expression quantitative trait loci (eQTLs) and protein abundance QTLs to annotate human single nucleotide polymorphisms (SNPs) and other common small variants.
• Variant-to-Gene Functional Annotation: Associates genetic variants with changes in gene expression and protein levels.
• Linkage Disequilibrium Incorporation: Incorporates linkage disequilibrium (LD) information to refine variant annotations and account for correlated variants.
• Reverse Gene Search: Enables gene-centered queries to retrieve associated QTLs.
• Cis-Distance Reevaluation: Evaluates base pair distances between eQTLs and target genes, reassessing the conventional 1,000,000 base pair cis-regulatory threshold and capturing potential trans-eQTL effects.
• Tissue-Specific Gene Ranking: Ranks genes by consistency of significant eQTL signals across multiple tissue-specific studies, highlighting housekeeping and highly expressed genes.

Scientific Applications:

• GWAS Functional Interpretation: Identifies candidate functional variants and target genes influencing gene expression and protein abundance in complex trait studies.
• Variant-to-Gene Mapping: Resolves genetic variant-to-gene relationships using LD-aware QTL annotation.

Methodology:

Integrates multiple QTL databases into a unified framework for batch GWAS variant annotation; computes base pair distances between significant eQTLs and target genes; incorporates linkage disequilibrium; and ranks genes based on cross-tissue consistency of eQTL signals.