COMBATdb: a database for the COVID-19 Multi-Omics Blood ATlas

Area of Science:

• Immunology
• Genomics
• Proteomics
• Infectious Diseases

Background:

• Understanding the immune response to SARS-CoV-2 is crucial for developing targeted therapies and precision medicine.
• Individual variations in immune response necessitate comprehensive multi-modal data analysis.

Purpose of the Study:

• To present COMBATdb, a database for the COvid-19 Multi-omics Blood ATlas (COMBAT) project.
• To enable exploration of multi-modal datasets for COVID-19 research.
• To facilitate comparison of immune responses across different diseases.

Main Methods:

• Collected multi-modal datasets including transcriptomics, proteomics, epigenomics, and single-cell multi-omics.
• Utilized immune repertoire sequencing, flow cytometry, and mass cytometry.
• Integrated cohort metadata for comprehensive analysis.

Main Results:

• COMBATdb provides processed data accessible via browse, search, download, calculation, and visualization tools.
• The database allows exploration across samples, cell types, genes, and proteins.
• Facilitates cross-modal data analysis for deeper insights.

Conclusions:

• COMBATdb enhances the ability to study COVID-19 pathogenesis.
• The database aids in understanding shared and specific immune features with other infectious diseases.
• Supports research into precision medicine approaches for infectious diseases.