dbGAP

dbGAP archives and distributes human genotype and phenotype datasets, including summary-level and controlled-access individual-level data, to support research into genotype–phenotype relationships.

Key Features:

• Hierarchical Structure: Organized hierarchically with accessioned objects, phenotypes represented as variables and datasets, molecular assay data, analyses, and related documents.
• Molecular Assay Data: Contains Single Nucleotide Polymorphisms (SNPs), Expression Array data, Sequence information, and Epigenomic marks.
• Public Metadata and Summary-Level Data: Provides publicly available metadata, study summary-level data, and related documents for submitted studies.
• Controlled Access to Individual-Level Data: Individual-level genetic and phenotypic data are available under controlled access to protect participant privacy and meet ethical requirements.
• Curation and Metadata Standards: Applies curation and archiving practices to enforce high-quality metadata standards for archived studies.

Scientific Applications:

• Research Domains: Supports studies across genetics, genomics, epidemiology, and personalized medicine.
• Variant Discovery and Association Studies: Enables identification of genetic variants associated with diseases using SNP and sequence data.
• Gene Expression Analysis: Supports analysis of Expression Array data to characterize gene expression patterns.
• Epigenetics: Facilitates investigation of epigenomic marks and epigenetic modifications.

Methodology:

dbGAP curates and archives submitted study data with enforced metadata standards, maintains summary-level and controlled-access individual-level datasets, and provides tools for data access and analysis within a controlled environment.