Article: A knowledge-based weighting framework to boost the power of genome-wide association studies
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- Publisher Website: 10.1371/journal.pone.0014480
- Scopus: eid_2-s2.0-79251484337
- PMID: 21217833
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| Title | A knowledge-based weighting framework to boost the power of genome-wide association studies | ||||||
|---|---|---|---|---|---|---|---|
| Authors | Li, MX1 Sham, PC1 Cherny, SS1 Song, YQ1 | ||||||
| Issue Date | 2010 | ||||||
| Publisher | Public 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?] DOI: http://dx.doi.org/10.1371/journal.pone.0014480 | ||||||
| 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. | ||||||
| ISSN | 1932-6203 2011 Impact Factor: 4.092 2011 SCImago Journal Rankings: 0.519 | ||||||
| DOI | http://dx.doi.org/10.1371/journal.pone.0014480 | ||||||
| ISI Accession Number ID | WOS:000285838900009
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. | ||||||
| PubMed Central ID | PMC3013112 | ||||||
| References | References in Scopus | ||||||
| Grants | Fine mapping candidate loci for nasopharyngeal carcinoma (NPC) in southern Chinese specifically linked to EBV aetiopathogenesis |
| dc.contributor.author | Li, MX | ||||||
|---|---|---|---|---|---|---|---|
| dc.contributor.author | Sham, PC | ||||||
| dc.contributor.author | Cherny, SS | ||||||
| dc.contributor.author | Song, YQ | ||||||
| dc.date.accessioned | 2011-07-27T01:25:59Z | ||||||
| dc.date.available | 2011-07-27T01:25:59Z | ||||||
| dc.date.issued | 2010 | ||||||
| dc.description.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. | ||||||
| dc.description.grant | Fine mapping candidate loci for nasopharyngeal carcinoma (NPC) in southern Chinese specifically linked to EBV aetiopathogenesis | ||||||
| dc.description.grantcode | 99533 | ||||||
| dc.description.nature | published_or_final_version | ||||||
| dc.identifier.citation | Plos One, 2010, v. 5 n. 12 [How to Cite?] DOI: http://dx.doi.org/10.1371/journal.pone.0014480 | ||||||
| dc.identifier.citeulike | 8501520 | ||||||
| dc.identifier.doi | http://dx.doi.org/10.1371/journal.pone.0014480 | ||||||
| dc.identifier.hkuros | 188454 | ||||||
| dc.identifier.hkuros | 186079 | ||||||
| dc.identifier.isi | WOS:000285838900009
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. | ||||||
| dc.identifier.issn | 1932-6203 2011 Impact Factor: 4.092 2011 SCImago Journal Rankings: 0.519 | ||||||
| dc.identifier.issue | 12 | ||||||
| dc.identifier.openurl | | ||||||
| dc.identifier.pmcid | PMC3013112 | ||||||
| dc.identifier.pmid | 21217833 | ||||||
| dc.identifier.scopus | eid_2-s2.0-79251484337 | ||||||
| dc.identifier.uri | http://hdl.handle.net/10722/135018 | ||||||
| dc.identifier.volume | 5 | ||||||
| dc.language | eng | ||||||
| dc.publisher | Public Library of Science. The Journal's web site is located at http://www.plosone.org/home.action | ||||||
| dc.publisher.place | United States | ||||||
| dc.relation.ispartof | PLoS ONE | ||||||
| dc.relation.references | References in Scopus | ||||||
| dc.rights | Creative Commons: Attribution 3.0 Hong Kong License | ||||||
| dc.subject.mesh | Alzheimer Disease - genetics | ||||||
| dc.subject.mesh | Binding Sites | ||||||
| dc.subject.mesh | Computational Biology - methods | ||||||
| dc.subject.mesh | Genome-Wide Association Study | ||||||
| dc.subject.mesh | Polymorphism, Single Nucleotide | ||||||
| dc.title | A knowledge-based weighting framework to boost the power of genome-wide association studies | ||||||
| dc.type | Article |
Author Affiliations
- The University of Hong Kong