Affiliation
Department of Mathematics, The University of Arizona, Tucson, AZ 85721, USAInterdisciplinary Program in Statistics, The University of Arizona, Tucson, AZ 85721, USA
Issue Date
2011
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BioMed CentralCitation
Niu et al. BMC Proceedings 2011, 5(Suppl 9):S108 http://www.biomedcentral.com/1753-6561/5/S9/S108Journal
BMC ProceedingsRights
© 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
1753-6561Version
Final published versionAdditional Links
http://www.biomedcentral.com/1753-6561/5/S9/S108ae974a485f413a2113503eed53cd6c53
10.1186/1753-6561-5-S9-S108
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Except where otherwise noted, this item's license is described as © 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).