FAANG Data Portal

FAANG Data Portal provides centralized aggregation and organization of sample, sequencing, and analysis data from standardized multi-omic assays to enable functional annotation and comparative genomics of farmed and companion animal genomes.

Key Features:

• Data aggregation: Aggregates and organizes sample, sequencing, and analysis data produced by FAANG consortia.
• Multi-omic assay support: Houses standardized multi-omic assay datasets for functional genome annotation.
• Metadata validation and brokering: Performs metadata validation and brokering services to ensure submissions meet EMBL-EBI archive standards.
• Predictive search and filters: Provides predefined filters and predictive search capabilities for dataset discovery.
• Protocol catalogue: Maintains a detailed catalogue of sampling and analysis protocols.
• Publication linking: Automatically links datasets with associated publications.
• FAIR compliance: Implements Findable, Accessible, Interoperable, and Reusable (FAIR) data management principles.
• Scalability for emerging technologies: Plans to expand infrastructure to support single-cellomics, cell atlases, pangenomes, and phenotypic prediction models.
• Governance and curation: Governed and curated by the FAANG Data Coordination Centre at the European Bioinformatics Institute (EMBL-EBI).

Scientific Applications:

• Comparative genomics: Enables comparative analyses across terrestrial and aquatic animal species.
• Functional element annotation: Supports identification and annotation of functional genomic elements in farmed and companion animals.
• Agricultural improvement: Supports research aimed at improving farmed animal production, disease resistance, and genetic diversity.
• Integration of emerging data types: Facilitates incorporation of single-cellomics, cell atlas, pangenome, and phenotypic prediction model data into functional studies.

Methodology:

Aggregates and organizes FAANG consortia data, applies metadata validation and brokering for EMBL-EBI archives, implements predefined filters and predictive search for discovery, and automatically links datasets to publications.