Detection of rare functional variants using group ISIS

Persistent Link:
http://hdl.handle.net/10150/610089
Title:
Detection of rare functional variants using group ISIS
Author:
Niu, Yue; Hao, Ning; An, Lingling
Affiliation:
Department of Mathematics, The University of Arizona, Tucson, AZ 85721, USA; Interdisciplinary Program in Statistics, The University of Arizona, Tucson, AZ 85721, USA
Issue Date:
2011
Publisher:
BioMed Central
Citation:
Niu et al. BMC Proceedings 2011, 5(Suppl 9):S108 http://www.biomedcentral.com/1753-6561/5/S9/S108
Journal:
BMC Proceedings
Rights:
© 2011 Niu et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)
Collection Information:
This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.
Abstract:
Genome-wide association studies have been firmly established in investigations of the associations between common genetic variants and complex traits or diseases. However, a large portion of complex traits and diseases cannot be explained well by common variants. Detecting rare functional variants becomes a trend and a necessity. Because rare variants have such a small minor allele frequency (e.g., <0.05), detecting functional rare variants is challenging. Group iterative sure independence screening (ISIS), a fast group selection tool, was developed to select important genes and the single-nucleotide polymorphisms within. The performance of the group ISIS and group penalization methods is compared for detecting important genes in the Genetic Analysis Workshop 17 data. The results suggest that the group ISIS is an efficient tool to discover genes and single-nucleotide polymorphisms associated to phenotypes.
EISSN:
1753-6561
DOI:
10.1186/1753-6561-5-S9-S108
Version:
Final published version
Additional Links:
http://www.biomedcentral.com/1753-6561/5/S9/S108

Full metadata record

DC FieldValue Language
dc.contributor.authorNiu, Yueen
dc.contributor.authorHao, Ningen
dc.contributor.authorAn, Linglingen
dc.date.accessioned2016-05-20T08:58:19Z-
dc.date.available2016-05-20T08:58:19Z-
dc.date.issued2011en
dc.identifier.citationNiu et al. BMC Proceedings 2011, 5(Suppl 9):S108 http://www.biomedcentral.com/1753-6561/5/S9/S108en
dc.identifier.doi10.1186/1753-6561-5-S9-S108en
dc.identifier.urihttp://hdl.handle.net/10150/610089-
dc.description.abstractGenome-wide association studies have been firmly established in investigations of the associations between common genetic variants and complex traits or diseases. However, a large portion of complex traits and diseases cannot be explained well by common variants. Detecting rare functional variants becomes a trend and a necessity. Because rare variants have such a small minor allele frequency (e.g., <0.05), detecting functional rare variants is challenging. Group iterative sure independence screening (ISIS), a fast group selection tool, was developed to select important genes and the single-nucleotide polymorphisms within. The performance of the group ISIS and group penalization methods is compared for detecting important genes in the Genetic Analysis Workshop 17 data. The results suggest that the group ISIS is an efficient tool to discover genes and single-nucleotide polymorphisms associated to phenotypes.en
dc.language.isoenen
dc.publisherBioMed Centralen
dc.relation.urlhttp://www.biomedcentral.com/1753-6561/5/S9/S108en
dc.rights© 2011 Niu et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)en
dc.titleDetection of rare functional variants using group ISISen
dc.typeArticleen
dc.identifier.eissn1753-6561en
dc.contributor.departmentDepartment of Mathematics, The University of Arizona, Tucson, AZ 85721, USAen
dc.contributor.departmentInterdisciplinary Program in Statistics, The University of Arizona, Tucson, AZ 85721, USAen
dc.identifier.journalBMC Proceedingsen
dc.description.collectioninformationThis item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
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