echolocatoR

echolocatoR performs statistical and functional fine-mapping by integrating multiple fine-mapping tools and genomic annotations to identify and test enrichment of high-confidence causal consensus variants.

Key Features:

• R package implementation: Provided as an R package for programmatic execution within R workflows.
• Statistical and functional fine-mapping: Combines statistical fine-mapping approaches with functional annotation to prioritize causal variants.
• Integration of multiple fine-mapping tools: Aggregates an extensive suite of fine-mapping methods to derive consensus variant calls.
• High-confidence causal consensus variants: Identifies and reports variants supported across methods as high-confidence causal candidates.
• Enrichment testing: Tests for enrichment of identified causal variants in genomic annotations and datasets.
• Comprehensive dataset access: Integrates reference linkage disequilibrium (LD) panels, quantitative trait loci (QTL), genome-wide annotations, and cell-type-specific epigenomics data.
• Input format: Accepts GWAS summary statistics as input for fine-mapping analyses.
• Visualization: Produces visualizations of fine-mapping results and prioritized variants.
• End-to-end analysis: Supports the workflow from variant identification through enrichment testing and visualization.

Scientific Applications:

• GWAS fine-mapping: Prioritizes causal variants in genome-wide association study loci.
• Genotype–phenotype interpretation: Integrates diverse genomic datasets to elucidate biological mechanisms underlying phenotypic traits.
• Complex trait genetics: Assists in uncovering genetic contributors to complex traits via consensus fine-mapping and enrichment analyses.

Methodology:

Performs statistical and functional fine-mapping by integrating multiple fine-mapping tools with reference LD panels, QTL, genome-wide annotations, and cell-type-specific epigenomic data, followed by enrichment testing and visualization to prioritize high-confidence causal consensus variants.