File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A knowledge-based weighting framework to boost the power of genome-wide association studies

TitleA knowledge-based weighting framework to boost the power of genome-wide association studies
Authors
Issue Date2010
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
Plos One, 2010, v. 5 n. 12 How to Cite?
Abstract
Background: We are moving to second-wave analysis of genome-wide association studies (GWAS), characterized by comprehensive bioinformatical and statistical evaluation of genetic associations. Existing biological knowledge is very valuable for GWAS, which may help improve their detection power particularly for disease susceptibility loci of moderate effect size. However, a challenging question is how to utilize available resources that are very heterogeneous to quantitatively evaluate the statistic significances. Methodology/Principal Findings: We present a novel knowledge-based weighting framework to boost power of the GWAS and insightfully strengthen their explorative performance for follow-up replication and deep sequencing. Built upon diverse integrated biological knowledge, this framework directly models both the prior functional information and the association significances emerging from GWAS to optimally highlight single nucleotide polymorphisms (SNPs) for subsequent replication. In the theoretical calculation and computer simulation, it shows great potential to achieve extra over 15% power to identify an association signal of moderate strength or to use hundreds of whole-genome subjects fewer to approach similar power. In a case study on late-onset Alzheimer disease (LOAD) for a proof of principle, it highlighted some genes, which showed positive association with LOAD in previous independent studies, and two important LOAD related pathways. These genes and pathways could be originally ignored due to involved SNPs only having moderate association significance. Conclusions/Significance: With user-friendly implementation in an open-source Java package, this powerful framework will provide an important complementary solution to identify more true susceptibility loci with modest or even small effect size in current GWAS for complex diseases. © 2010 Li et al.
Persistent Identifierhttp://hdl.handle.net/10722/135018
ISSN
2013 Impact Factor: 3.534
2013 SCImago Journal Rankings: 1.724
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Research Grant Council of Hong KongHKU7688/05M
HKU7752/08M
Research Fund for the Control of Infectious Diseases (RFCID)08070652
Funding Information:

This work was supported by the Research Grant Council of Hong Kong (HKU7688/05M and HKU7752/08M, YQS) and the Research Fund for the Control of Infectious Diseases (RFCID) (no. 08070652, YQS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References
Grants

 

Author Affiliations
  1. The University of Hong Kong
DC FieldValueLanguage
dc.contributor.authorLi, MXen_HK
dc.contributor.authorSham, PCen_HK
dc.contributor.authorCherny, SSen_HK
dc.contributor.authorSong, YQen_HK
dc.date.accessioned2011-07-27T01:25:59Z-
dc.date.available2011-07-27T01:25:59Z-
dc.date.issued2010en_HK
dc.identifier.citationPlos One, 2010, v. 5 n. 12en_HK
dc.identifier.issn1932-6203en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135018-
dc.description.abstractBackground: We are moving to second-wave analysis of genome-wide association studies (GWAS), characterized by comprehensive bioinformatical and statistical evaluation of genetic associations. Existing biological knowledge is very valuable for GWAS, which may help improve their detection power particularly for disease susceptibility loci of moderate effect size. However, a challenging question is how to utilize available resources that are very heterogeneous to quantitatively evaluate the statistic significances. Methodology/Principal Findings: We present a novel knowledge-based weighting framework to boost power of the GWAS and insightfully strengthen their explorative performance for follow-up replication and deep sequencing. Built upon diverse integrated biological knowledge, this framework directly models both the prior functional information and the association significances emerging from GWAS to optimally highlight single nucleotide polymorphisms (SNPs) for subsequent replication. In the theoretical calculation and computer simulation, it shows great potential to achieve extra over 15% power to identify an association signal of moderate strength or to use hundreds of whole-genome subjects fewer to approach similar power. In a case study on late-onset Alzheimer disease (LOAD) for a proof of principle, it highlighted some genes, which showed positive association with LOAD in previous independent studies, and two important LOAD related pathways. These genes and pathways could be originally ignored due to involved SNPs only having moderate association significance. Conclusions/Significance: With user-friendly implementation in an open-source Java package, this powerful framework will provide an important complementary solution to identify more true susceptibility loci with modest or even small effect size in current GWAS for complex diseases. © 2010 Li et al.en_HK
dc.languageengen_US
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.actionen_HK
dc.relation.ispartofPLoS ONEen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject.meshAlzheimer Disease - genetics-
dc.subject.meshBinding Sites-
dc.subject.meshComputational Biology - methods-
dc.subject.meshGenome-Wide Association Study-
dc.subject.meshPolymorphism, Single Nucleotide-
dc.titleA knowledge-based weighting framework to boost the power of genome-wide association studiesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1932-6203&volume=5&issue=12, article no. e14480&spage=&epage=&date=2010&atitle=A+knowledge-based+weighting+framework+to+boost+the+power+of+genome-wide+association+studies-
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.emailCherny, SS: cherny@hku.hken_HK
dc.identifier.emailSong, YQ: songy@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.identifier.authorityCherny, SS=rp00232en_HK
dc.identifier.authoritySong, YQ=rp00488en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0014480en_HK
dc.identifier.pmid21217833en_HK
dc.identifier.pmcidPMC3013112-
dc.identifier.scopuseid_2-s2.0-79251484337en_HK
dc.identifier.hkuros188454en_US
dc.identifier.hkuros186079-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79251484337&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume5en_HK
dc.identifier.issue12en_HK
dc.identifier.isiWOS:000285838900009-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectFine mapping candidate loci for nasopharyngeal carcinoma (NPC) in southern Chinese specifically linked to EBV aetiopathogenesis-
dc.identifier.scopusauthoridLi, MX=35205389900en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.scopusauthoridCherny, SS=7004670001en_HK
dc.identifier.scopusauthoridSong, YQ=7404921212en_HK
dc.identifier.citeulike8501520-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats