AffiliationDepartment of Mathematics, The University of Arizona, Tucson, AZ 85721, USA
Interdisciplinary Program in Statistics, The University of Arizona, Tucson, AZ 85721, USA
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CitationNiu et al. BMC Proceedings 2011, 5(Suppl 9):S108 http://www.biomedcentral.com/1753-6561/5/S9/S108
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)
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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.
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