A comprehensive database for GWAS¬identified human genetic variants: an update of GWASdb

Abstract

INTRODUCTION: During the past few years, more than 10,000 single-nucleotide polymorphisms (SNPs) that associated with traits/diseases have been discovered through genome-wide association studies (GWASs). With the rapid development of SNP detection technology, even more SNPs are to be uncovered in the near future. Accordingly, a well-organized source to collect and annotate these valuable trait/disease associated SNPs (TASs) obtained from multi-million-dollar projects is in great need. GWASdb (http://jjwanglab.org/gwasdb) has satisfyingly served as such a source for the community since its first launch in 2011. METHODS AND RESULTS: Here, we report recent updates of GWASdb, including new data and novel features: (1) Until the latest update (Sep 2014), 2,128 publicly available GWASs have been collected from PubMed papers, as well as other well-known sources including NHGRI GWAS Catalog, HuGE Navigator, PheGenI and NIH GRASP; (2) Moderate SNP-trait associations with p-value of less than 1E-3 were manually curated from each publication, and totally 224,454 TASs were selected in current database; (3) Over 1,100 trait/disease descriptions from original studies were manually mapped to well-defined ontologies including Human Phenotype Ontology (HPO), Disease Ontology (DO) and Disease Ontology Lite (DOLite); (4) Population information was curated for each study and classified into 8 ethnogeographic categories: European, African, East Asian, South Asian, Hispanic, Native American, Middle Eastern and Oceania; (5) More than 40 annotations were provided for each TAS by combing up-to-date data from various sources, including population haplotype (e.g. HapMap, 1000 Genomes), gene-based annotation (e.g. RefSeq), knowledge-based annotation (e.g. ENCODE ChIP-seq, eQTL), functional annotation (e.g. transcriptional factor binding site affinity), evolution annotation (e.g. dbPSHP) and disease-related annotation (e.g. OMIM); (6) User interface and visualization tools were also improved. CONCLUSIONS: To our knowledge, at the time of this update version, GWASdb collects the most GWAS publications and provides the most comprehensive data annotations in this field. GWASdb will be constantly updated in the future and continue to facilitate the in-depth investigation of association between human genetic variants and diseases.