Welcome to the RADB

Using the data in the database, please cite the article.  
Ruijie Zhang, Meiwei Luan, Zhenwei Shang, Lian Duan, Guoping Tang, Miao Shi, Wenhua Lv, Hongjie Zhu, Jin Li, Hongchao Lv, Mingming Zhang, Guiyou Liu, He Chen, Yongshuai Jiang. RADB: a database of rheumatoid arthritis-related polymorphisms. Database, 2014, 1–9.doi: 10.1093/database/bau090.
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   Rheumatoid arthritis (RA) is a systemic, inflammatory, autoimmune disorder affecting ~1% of the population. The genetic component of RA has been estimated to be between 50%-60%. Therefore, exploring genetic background of RA is very important.

   The aim of RADB is to effectively integrate and analyze all the RA-related genetic polymorphisms extracted from published papers. We manually extracted the rheumatoid arthritis (RA) related polymorphisms (e.g. single nucleotide polymorphism (SNP), HLA allele and microsatellite) from about 2,000 publications. After manually scanning the list, we extracted the important information from these reports, including basic information about the article (e.g., PubMed ID (PMID), title, and abstract), population information (e.g., country,region and sample size), and polymorphism information (e.g., polymorphism name, host gene, genotype, odds ratio (OR) with 95% confidence interval (CI), P-value, and risk allele).

   Currently, the RADB contains 3235 polymorphisms that are associated with 636 genes and refer to 68 countries. Data is divided into four categories: (i) susceptibility locus for RA; (ii) polymorphisms associated with particular clinical features of RA; (iii) polymorphisms associated with drug response in RA; and (iv) polymorphisms associated with a higher risk of CV disease in RA. Meanwhile, useful annotations, such as hyperlinks to dbSNP, GenBank, UCSC, Gene Ontology, and KEGG pathway, are included.

   To meet the needs of different users, we offer different ways to search our database, including searching by polymorphism, searching by gene, searching by population, searching by different types of research (including candidate gene linkage analysis studies, candidate gene association studies, and GWAS), and searching by chromosome.

   A tool for meta-analysis was developed to summarize the results of multiple studies. Users can directly perform meta-analyses on the polymorphisms in RADB. Users can choose the parameters, such as the type of study (e.g., case-control), the assumed risk allele, and the genetic model. In addition, users can either analyze just their own data or supplement it with RADB data.

   Anyone may view the RADB. Meanwhile, we welcome users to download data. If you have feedback or questions about the RADB, please feel free to contact us, your proposal will promote the upgrading of our database.

CopyRight © Group of Statistical Genetics, College of Bioinformatics Science and Technology, Harbin Medical University, China