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Two-Stage Approach for Identifying Single-Nucleotide Polymorphisms Associated with Rheumatoid Arthritis Using Random Forests and Bayesian Networks

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dc.contributor.author Meng, Yan en_US
dc.contributor.author Yang, Qiong en_US
dc.contributor.author Cuenco, Karen T en_US
dc.contributor.author Cupples, L Adrienne en_US
dc.contributor.author DeStefano, Anita L en_US
dc.contributor.author Lunetta, Kathryn L en_US
dc.date.accessioned 2012-01-09T20:53:17Z
dc.date.available 2012-01-09T20:53:17Z
dc.date.copyright 2007 en_US
dc.date.issued 2007-12-18 en_US
dc.identifier.citation Meng, Yan, Qiong Yang, Karen T Cuenco, L Adrienne Cupples, Anita L DeStefano, Kathryn L Lunetta. "Two-stage approach for identifying single-nucleotide polymorphisms associated with rheumatoid arthritis using random forests and Bayesian networks" BMC Proceedings 1(Suppl 1):S56. (2007) en_US
dc.identifier.issn 1753-6561 en_US
dc.identifier.uri http://hdl.handle.net/2144/2900
dc.description.abstract We used the simulated data set from Genetic Analysis Workshop 15 Problem 3 to assess a two-stage approach for identifying single-nucleotide polymorphisms (SNPs) associated with rheumatoid arthritis (RA). In the first stage, we used random forests (RF) to screen large amounts of genetic data using the variable importance measure, which takes into account SNP interaction effects as well as main effects without requiring model specification. We used the simulated 9187 SNPs mimicking a 10 K SNP chip, along with covariates DR (the simulated DRB1 gentoype), smoking, and sex as input to the RF analyses with a training set consisting of 750 unrelated RA cases and 750 controls. We used an iterative RF screening procedure to identify a smaller set of variables for further analysis. In the second stage, we used the software program CaMML for producing Bayesian networks, and developed complex etiologic models for RA risk using the variables identified by our RF screening procedure. We evaluated the performance of this method using independent test data sets for up to 100 replicates. en_US
dc.description.sponsorship Fonds de la Recherche en Santé; National Institutes of Health (R01 AG09029, R01 AG017173, R01 NS36711-04); National Heart, Lung and Blood Institute's Framingham Heart Study (N01-HC-25195); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (S10 RR163736-01A1) en_US
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.rights Copyright 2007 Meng 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), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. en_US
dc.rights.uri http://creativecommons.org/licenses/by/2.0 en_US
dc.title Two-Stage Approach for Identifying Single-Nucleotide Polymorphisms Associated with Rheumatoid Arthritis Using Random Forests and Bayesian Networks en_US
dc.type article en_US
dc.identifier.pubmedid 18466556 en_US
dc.identifier.pmcid 2367609 en_US


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Copyright 2007 Meng 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), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Except where otherwise noted, this item's license is described as Copyright 2007 Meng 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), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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