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GWASdb: a database for human genetic variants identified by genome-wide association studies
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, suc...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245026/ https://www.ncbi.nlm.nih.gov/pubmed/22139925 http://dx.doi.org/10.1093/nar/gkr1182 |
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author | Li, Mulin Jun Wang, Panwen Liu, Xiaorong Lim, Ee Lyn Wang, Zhangyong Yeager, Meredith Wong, Maria P. Sham, Pak Chung Chanock, Stephen J. Wang, Junwen |
author_facet | Li, Mulin Jun Wang, Panwen Liu, Xiaorong Lim, Ee Lyn Wang, Zhangyong Yeager, Meredith Wong, Maria P. Sham, Pak Chung Chanock, Stephen J. Wang, Junwen |
author_sort | Li, Mulin Jun |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3245026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-32450262012-01-10 GWASdb: a database for human genetic variants identified by genome-wide association studies Li, Mulin Jun Wang, Panwen Liu, Xiaorong Lim, Ee Lyn Wang, Zhangyong Yeager, Meredith Wong, Maria P. Sham, Pak Chung Chanock, Stephen J. Wang, Junwen Nucleic Acids Res Articles 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. Oxford University Press 2012-01 2011-12-01 /pmc/articles/PMC3245026/ /pubmed/22139925 http://dx.doi.org/10.1093/nar/gkr1182 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Li, Mulin Jun Wang, Panwen Liu, Xiaorong Lim, Ee Lyn Wang, Zhangyong Yeager, Meredith Wong, Maria P. Sham, Pak Chung Chanock, Stephen J. Wang, Junwen GWASdb: a database for human genetic variants identified by genome-wide association studies |
title | GWASdb: a database for human genetic variants identified by genome-wide association studies |
title_full | GWASdb: a database for human genetic variants identified by genome-wide association studies |
title_fullStr | GWASdb: a database for human genetic variants identified by genome-wide association studies |
title_full_unstemmed | GWASdb: a database for human genetic variants identified by genome-wide association studies |
title_short | GWASdb: a database for human genetic variants identified by genome-wide association studies |
title_sort | gwasdb: a database for human genetic variants identified by genome-wide association studies |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245026/ https://www.ncbi.nlm.nih.gov/pubmed/22139925 http://dx.doi.org/10.1093/nar/gkr1182 |
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