CNSA

CNSA archives and curates omics data generated by high-throughput sequencing technologies for life and health sciences as part of the China National GeneBank (CNGB).

Key Features:

• Data Organization: Organizes data into six primary objects—Project, Sample, Experiment, Run, Assembly, and Variation—to structure sequencing data and metadata.
• Correlation Model: Implements a correlation model linking living samples with sample information and analytical data across projects to trace data provenance.
• Data Standards Compliance: Adheres to widely recognized life-science data standards to ensure compatibility with other scientific databases and tools.
• Comprehensive Repository: Stores raw sequencing data, analytical data, and associated metadata within a curated archive.
• Biocuration: Applies meticulous biocuration processes to ensure accuracy and completeness of archived datasets.

Scientific Applications:

• Genomics: Supports genomics research by archiving sequencing reads, assemblies, and variation data for comparative and functional analyses.
• Transcriptomics: Provides archived sequencing and metadata resources to enable transcriptome analyses.
• Proteomics: Houses analytical datasets and associated metadata that can support proteomics investigations.
• Metabolomics: Contains omics datasets and metadata that can be integrated for metabolomics research.
• Disease and Therapeutic Research: Enables investigation of disease pathways and development of therapeutic strategies through integrated omics datasets.

Methodology:

Biocuration processes, a platform architecture designed to handle large volumes of high-dimensional sequencing and analytical data, and a correlation model linking living samples, sample information, and analytical outputs.