RABC: Rheumatoid Arthritis Bioinformatics Center.
Haiyan ChenJing XuSiyu WeiZhe JiaChen SunJingxuan KangXuying GuoNan ZhangJunxian TaoYu DongChen ZhangYingnan MaWenhua LvHongsheng TianShuo BiHongchao LvChen HuangFanwu KongGuoping TangYongshuai JiangMingming ZhangPublished in: Nucleic acids research (2022)
Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.
Keyphrases
- rheumatoid arthritis
- electronic health record
- disease activity
- big data
- genome wide
- single cell
- ankylosing spondylitis
- healthcare
- dna methylation
- systematic review
- gene expression
- systemic lupus erythematosus
- high throughput
- rna seq
- data analysis
- adverse drug
- social media
- low cost
- transcription factor
- genome wide identification
- deep learning