OpenGWAS

OpenGWAS provides programmatic access to harmonized genome-wide association study (GWAS) summary statistics for large-scale analysis of genetic associations across human phenotypes and diseases.

Key Features:

• Data Integration and Harmonization: Imports complete GWAS summary datasets from diverse sources and formats and harmonizes variant identifiers and alleles against dbSNP and the human genome reference sequence.
• Extensive Data Repository: Aggregates 126 billion genetic associations from 14,582 complete GWAS datasets spanning a wide range of human phenotypes and disease outcomes across diverse populations.
• Analytical Integration: Provides R and Python packages that connect the harmonized summary statistics to analytical workflows supporting Mendelian randomization, genetic colocalisation analysis, fine mapping, genetic correlation studies, and locus visualization.

Scientific Applications:

• Causal inference (Mendelian randomization): Enables use of harmonized summary statistics to perform Mendelian randomization analyses for assessing causal relationships between exposures and outcomes.
• Colocalisation and fine mapping: Supports colocalisation analyses and fine-mapping efforts to resolve shared causal variants at loci associated with traits and diseases.
• Genetic architecture and correlation studies: Facilitates genetic correlation and cross-trait analyses to characterize shared genetic architecture among phenotypes.
• Cross-phenotype and population analyses: Allows exploration of genetic associations across diverse phenotypes and populations to inform understanding of complex traits and disease mechanisms.

Methodology:

Imports GWAS summary datasets and harmonizes them against dbSNP and the human genome reference sequence, standardizes result and metadata formats, and generates summary reports.