Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Jan;40(Database issue):D1047-54.
doi: 10.1093/nar/gkr1182. Epub 2011 Dec 1.

GWASdb: A Database for Human Genetic Variants Identified by Genome-Wide Association Studies

Affiliations
Free PMC article

GWASdb: A Database for Human Genetic Variants Identified by Genome-Wide Association Studies

Mulin Jun Li et al. Nucleic Acids Res. .
Free PMC article

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.

Figures

Figure 1.
Figure 1.
The overview of GWASdb database design. GWASdb consists of three main functions: precise scientific curation and resources integration on GWAS, comprehensive annotation of genetic variants and disease-oriented analysis in terms of DOLite and HPO.
Figure 2.
Figure 2.
Classifications of GVs from the genic regions and according to the traits/diseases in GWASdb. (a) The proportion of GV/gene transcripts with different functional properties in the genic regions (total representing 43.5% of all GVs in GWASdb). (b) The Top 15 traits/diseases which have the most significant GVs in database based on DOLite catalog.
Figure 3.
Figure 3.
Illustration of the circular GWAS plot. (a) Overview of the circular GWAS plot, dots show the top two GVs for each study. (b) A description of each of the components in the plot.

Similar articles

See all similar articles

Cited by 84 articles

See all "Cited by" articles

References

    1. The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature. 2010;467:1061–1073. - PMC - PubMed
    1. Altshuler DM, Gibbs RA, Peltonen L, Dermitzakis E, Schaffner SF, Yu F, Bonnen PE, de Bakker PI, Deloukas P, Gabriel SB, et al. Integrating common and rare genetic variation in diverse human populations. Nature. 2010;467:52–58. - PMC - PubMed
    1. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, Manolio TA. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA. 2009;106:9362–9367. - PMC - PubMed
    1. Johnson AD, O'Donnell CJ. An open access database of genome-wide association results. BMC Med. Genet. 2009;10:6. - PMC - PubMed
    1. Thorisson GA, Lancaster O, Free RC, Hastings RK, Sarmah P, Dash D, Brahmachari SK, Brookes AJ. HGVbaseG2P: a central genetic association database. Nucleic Acids Res. 2009;37:D797–D802. - PMC - PubMed

Publication types

Feedback