RABC

RABC aggregates multi-omics and literature data for rheumatoid arthritis to enable biomarker discovery and molecular characterization.

Key Features:

• Extensive multi-omics data collection: RABC contains 175 datasets spanning transcriptome, epigenome, genome, and proteome sample sets.
• Diverse molecular data categories: The resource includes 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18,464 differentially DNA methylated (DNAm) genes, 1,764 KEGG pathways, 30,488 Gene Ontology (GO) terms, 74,334 single nucleotide polymorphisms (SNPs), 242,779 expression quantitative trait loci (eQTLs), 105 m6A-SNPs, and 18,491,669 meta-mQTLs.
• Integration of prior knowledge: RABC integrates seven types of rheumatoid arthritis molecular markers curated from nine public databases.
• Literature database: RABC includes 127,073 PubMed entries covering publications from 1972 to March 2022.

Scientific Applications:

• Pathogenesis studies: Multi-omics data enable investigation of molecular mechanisms underlying rheumatoid arthritis.
• Diagnostic marker identification: Cross-omics comparisons support discovery of candidate diagnostic biomarkers.
• Therapeutic target exploration: Integrated molecular and genetic datasets facilitate identification of potential therapeutic targets.

Methodology:

Datasets were systematically collected, categorized, and uniformly processed.