garfield

garfield integrates GWAS summary statistics with regulatory and functional genomic annotations to quantify enrichment of trait-associated variants in regulatory regions while adjusting for confounding genomic factors.

Key Features:

• Integration of Regulatory Annotations: Leverages catalogs of regulatory genomic regions from projects such as ENCODE and Roadmap to link GWAS signals to non-coding functional elements.
• Greedy Pruning of SNPs: Employs a greedy pruning strategy to reduce GWAS single nucleotide polymorphisms (SNPs) to a subset for enrichment analysis.
• Functional Overlap Annotation: Annotates pruned SNPs by their overlap with functional genomic regions to identify candidate regulatory features.
• Quantification of Fold Enrichment (FE): Calculates fold enrichment (FE) at multiple GWAS significance thresholds to measure over-representation of associations in annotations.
• Permutation Testing and Confounding Adjustment: Uses permutation testing to assess significance and adjusts for confounders including minor allele frequency (MAF), distance to transcription start sites (TSS), and number of linkage disequilibrium (LD) proxies.

Scientific Applications:

• Genetic architecture of complex traits: Assess contribution of regulatory regions to phenotypic variation and disease by quantifying enrichment of GWAS associations in functional annotations.
• Annotation-specific enrichment profiling: Characterize and compare enrichment patterns across different traits and regulatory annotations to reveal trait-specific regulatory mechanisms.

Methodology:

Integrates GWAS data with regulatory annotations (e.g., ENCODE, Roadmap); applies greedy SNP pruning; annotates SNPs by overlap with functional regions; computes fold enrichment across GWAS significance thresholds and evaluates significance via permutation testing while controlling for MAF, distance to TSS, and number of LD proxies.