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Conference Paper: A novel three-class ROC method for eQTL analysis

TitleA novel three-class ROC method for eQTL analysis
Authors
KeywordsExpression quantitative trait loci (eQTL)
Nonparametric
Normal distribution
Receiver operating characteristic (ROC)
Volume under surface (VUS)
Issue Date2010
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000424
Citation
The 2010 International Conference on Machine Learning and Cybernetics (ICMLC 2010), Qingdao, China, 11-14 July 2010. In Proceedings of the International Conference on Machine Learning and Cybernetics, 2010, v. 6, p. 3056-3061 How to Cite?
AbstractThe problem of identifying genetic factors underlying complex and quantitative traits such as height, weight and disease susceptibility in natural populations has become a major theme of research in recent years. Aiming at revealing the inter-dependency and causal relationship between the underlying genotypes and observed phenotypes, researchers from different areas have developed a variety of methods for expression quantitative trait loci (eQTL) mapping. Most of these methods rely on resampling-based algorithms that are computationally very expensive. To overcome the disadvantages of the current techniques, we propose a novel nonparametric method based on the volume under surface (VUS) within the framework of three-class receiver operating characteristic (ROC) analysis. With the fast algorithms developed, we can reduce the computation time of the genomewide analysis from several months down to several days. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/126161
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorXu, Wen_HK
dc.contributor.authorChen, Pen_HK
dc.contributor.authorHung, YSen_HK
dc.contributor.authorKung, SYen_HK
dc.date.accessioned2010-10-31T12:13:06Z-
dc.date.available2010-10-31T12:13:06Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 2010 International Conference on Machine Learning and Cybernetics (ICMLC 2010), Qingdao, China, 11-14 July 2010. In Proceedings of the International Conference on Machine Learning and Cybernetics, 2010, v. 6, p. 3056-3061en_HK
dc.identifier.isbn978-142446526-2-
dc.identifier.urihttp://hdl.handle.net/10722/126161-
dc.description.abstractThe problem of identifying genetic factors underlying complex and quantitative traits such as height, weight and disease susceptibility in natural populations has become a major theme of research in recent years. Aiming at revealing the inter-dependency and causal relationship between the underlying genotypes and observed phenotypes, researchers from different areas have developed a variety of methods for expression quantitative trait loci (eQTL) mapping. Most of these methods rely on resampling-based algorithms that are computationally very expensive. To overcome the disadvantages of the current techniques, we propose a novel nonparametric method based on the volume under surface (VUS) within the framework of three-class receiver operating characteristic (ROC) analysis. With the fast algorithms developed, we can reduce the computation time of the genomewide analysis from several months down to several days. © 2010 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000424-
dc.relation.ispartof2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010en_HK
dc.rightsProceedings of the International Conference on Machine Learning and Cybernetics. Copyright © IEEE.-
dc.rights©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectExpression quantitative trait loci (eQTL)en_HK
dc.subjectNonparametricen_HK
dc.subjectNormal distributionen_HK
dc.subjectReceiver operating characteristic (ROC)en_HK
dc.subjectVolume under surface (VUS)en_HK
dc.titleA novel three-class ROC method for eQTL analysisen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailXu, W: wcxu@eee.hku.hken_HK
dc.identifier.emailHung, YS: yshung@hkucc.hku.hken_HK
dc.identifier.authorityXu, W=rp00198en_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICMLC.2010.5580746en_HK
dc.identifier.scopuseid_2-s2.0-78149293286en_HK
dc.identifier.hkuros175050en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78149293286&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.spage3056en_HK
dc.identifier.epage3061en_HK
dc.publisher.placeUnited States-
dc.description.otherThe 2010 International Conference on Machine Learning and Cybernetics (ICMLC 2010), Qingdao, China, 11-14 July 2010. In Proceedings of the International Conference on Machine Learning and Cybernetics, 2010, v. 6, p. 3056-3061-
dc.identifier.scopusauthoridXu, W=7404428876en_HK
dc.identifier.scopusauthoridChen, P=36616885900en_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK
dc.identifier.scopusauthoridKung, SY=7102989364en_HK

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