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GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications
Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in...
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Published in: | Nucleic acids research 2013-07, Vol.41 (Web Server issue), p.W150-W158 |
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creator | Li, Mulin Jun Wang, Lily Yan Xia, Zhengyuan Sham, Pak Chung Wang, Junwen |
description | Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype-phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at http://jjwanglab.org/gwas3d. |
doi_str_mv | 10.1093/nar/gkt456 |
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Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype-phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at http://jjwanglab.org/gwas3d.</description><identifier>ISSN: 0305-1048</identifier><identifier>EISSN: 1362-4962</identifier><identifier>DOI: 10.1093/nar/gkt456</identifier><identifier>PMID: 23723249</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Chromosomes, Human - metabolism ; Disease - genetics ; Genetic Variation ; Genome-Wide Association Study ; Histones - metabolism ; Humans ; Internet ; Molecular Sequence Annotation ; Nucleotide Motifs ; Regulatory Elements, Transcriptional ; Software ; Transcription Factors - metabolism</subject><ispartof>Nucleic acids research, 2013-07, Vol.41 (Web Server issue), p.W150-W158</ispartof><rights>The Author(s) 2013. Published by Oxford University Press. 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c444t-ae853c8f76df3a8be44f8b14a65ff74179246fe166291d4e144ba28e66a503893</citedby><cites>FETCH-LOGICAL-c444t-ae853c8f76df3a8be44f8b14a65ff74179246fe166291d4e144ba28e66a503893</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692118/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692118/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23723249$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Mulin Jun</creatorcontrib><creatorcontrib>Wang, Lily Yan</creatorcontrib><creatorcontrib>Xia, Zhengyuan</creatorcontrib><creatorcontrib>Sham, Pak Chung</creatorcontrib><creatorcontrib>Wang, Junwen</creatorcontrib><title>GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications</title><title>Nucleic acids research</title><addtitle>Nucleic Acids Res</addtitle><description>Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype-phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at http://jjwanglab.org/gwas3d.</description><subject>Chromosomes, Human - metabolism</subject><subject>Disease - genetics</subject><subject>Genetic Variation</subject><subject>Genome-Wide Association Study</subject><subject>Histones - metabolism</subject><subject>Humans</subject><subject>Internet</subject><subject>Molecular Sequence Annotation</subject><subject>Nucleotide Motifs</subject><subject>Regulatory Elements, Transcriptional</subject><subject>Software</subject><subject>Transcription Factors - metabolism</subject><issn>0305-1048</issn><issn>1362-4962</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNpVkU9v1DAQxS0EokvhwgdAPiJEqP9MvAkHpKotpVKlHgBxtBxnnDUkdrGdRfs1-MRNu6Wip5Hm_d6bkR4hrzn7wFkrj4JJR8OvArV6QlZcKlFBq8RTsmKS1RVn0ByQFzn_ZIwDr-E5ORByLaSAdkX-nv84_ipPP9JTLGiLDwPdzJMJNOEwj6bEtKNbk7wJJdNuR30oOCRT_BapCWbcZZ9pdHTAECes_vh-2eccrV-YGPJ7ajcpTjEv6p05GXsnLO6ebnwuMSCdYu-dt3vLS_LMmTHjq_t5SL5_Pvt28qW6vDq_ODm-rCwAlMpgU0vbuLXqnTRNhwCu6TgYVTu3Br5uBSiHXCnR8h6QA3RGNKiUqZlsWnlIPu1zr-duwt5iKMmM-jr5yaSdjsbrx0rwGz3ErZaqFZw3S8Db-4AUf8-Yi558tjiOJmCcs-YgFGM1KL6g7_aoTTHnhO7hDGf6tkS9lKj3JS7wm_8fe0D_tSZvACvincs</recordid><startdate>20130701</startdate><enddate>20130701</enddate><creator>Li, Mulin Jun</creator><creator>Wang, Lily Yan</creator><creator>Xia, Zhengyuan</creator><creator>Sham, Pak Chung</creator><creator>Wang, Junwen</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20130701</creationdate><title>GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications</title><author>Li, Mulin Jun ; Wang, Lily Yan ; Xia, Zhengyuan ; Sham, Pak Chung ; Wang, Junwen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c444t-ae853c8f76df3a8be44f8b14a65ff74179246fe166291d4e144ba28e66a503893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Chromosomes, Human - metabolism</topic><topic>Disease - genetics</topic><topic>Genetic Variation</topic><topic>Genome-Wide Association Study</topic><topic>Histones - metabolism</topic><topic>Humans</topic><topic>Internet</topic><topic>Molecular Sequence Annotation</topic><topic>Nucleotide Motifs</topic><topic>Regulatory Elements, Transcriptional</topic><topic>Software</topic><topic>Transcription Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Mulin Jun</creatorcontrib><creatorcontrib>Wang, Lily Yan</creatorcontrib><creatorcontrib>Xia, Zhengyuan</creatorcontrib><creatorcontrib>Sham, Pak Chung</creatorcontrib><creatorcontrib>Wang, Junwen</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nucleic acids research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Mulin Jun</au><au>Wang, Lily Yan</au><au>Xia, Zhengyuan</au><au>Sham, Pak Chung</au><au>Wang, Junwen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications</atitle><jtitle>Nucleic acids research</jtitle><addtitle>Nucleic Acids Res</addtitle><date>2013-07-01</date><risdate>2013</risdate><volume>41</volume><issue>Web Server issue</issue><spage>W150</spage><epage>W158</epage><pages>W150-W158</pages><issn>0305-1048</issn><eissn>1362-4962</eissn><abstract>Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype-phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at http://jjwanglab.org/gwas3d.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>23723249</pmid><doi>10.1093/nar/gkt456</doi><oa>free_for_read</oa></addata></record> |
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subjects | Chromosomes, Human - metabolism Disease - genetics Genetic Variation Genome-Wide Association Study Histones - metabolism Humans Internet Molecular Sequence Annotation Nucleotide Motifs Regulatory Elements, Transcriptional Software Transcription Factors - metabolism |
title | GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications |
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