GWASdb: A database for human genetic variants identified by genome-wide association studies

Mulin Jun Li, Panwen Wang, Xiaorong Liu, Ee Lyn Lim, Zhangyong Wang, Meredith Yeager, Maria P. Wong, Pak Chung Sham, Stephen J. Chanock, Junwen Wang

Research output: Contribution to journalArticlepeer-review

128 Scopus citations

Abstract

Recent advances in genome-wide association studies (GWAS) have enabled us to identify thousands of genetic variants (GVs) that are associated with human diseases. As next-generation sequencing technologies become less expensive, more GVs will be discovered in the near future. Existing databases, such as NHGRI GWAS Catalog, collect GVs with only genome-wide level significance. However, many true disease susceptibility loci have relatively moderate P values and are not included in these databases. We have developed GWASdb that contains 20 times more data than the GWAS Catalog and includes less significant GVs (P < 1.0 × 10 -3) manually curated from the literature. In addition, GWASdb provides comprehensive functional annotations for each GV, including genomic mapping information, regulatory effects (transcription factor binding sites, microRNA target sites and splicing sites), amino acid substitutions, evolution, gene expression and disease associations. Furthermore, GWASdb classifies these GVs according to diseases using Disease-Ontology Lite and Human Phenotype Ontology. It can conduct pathway enrichment and PPI network association analysis for these diseases. GWASdb provides an intuitive, multifunctional database for biologists and clinicians to explore GVs and their functional inferences. It is freely available at http://jjwanglab.org/gwasdb and will be updated frequently.

Original languageEnglish (US)
Pages (from-to)D1047-D1054
JournalNucleic acids research
Volume40
Issue numberD1
DOIs
StatePublished - Jan 2012

ASJC Scopus subject areas

  • Genetics

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