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dc.contributor.authorMeng, Yanen_US
dc.contributor.authorMa, Qianlien_US
dc.contributor.authorYu, Yien_US
dc.contributor.authorFarrell, Johnen_US
dc.contributor.authorFarrer, Lindsay A.en_US
dc.contributor.authorWilcox, Marsha A.en_US
dc.date.accessioned2012-01-09T20:53:15Z
dc.date.available2012-01-09T20:53:15Z
dc.date.copyright2005
dc.date.issued2005-12-30
dc.identifier.citationMeng, Yan, Qianli Ma, Yi Yu, John Farrell, Lindsay A Farrer, Marsha A Wilcox. "Multifactor-dimensionality reduction versus family-based association tests in detecting susceptibility loci in discordant sib-pair studies" BMC Genetics 6(Suppl 1):S146. (2005)
dc.identifier.issn1471-2156
dc.identifier.urihttp://hdl.handle.net/2144/2897
dc.description.abstractComplex diseases are generally thought to be under the influence of multiple, and possibly interacting, genes. Many association methods have been developed to identify susceptibility genes assuming a single-gene disease model, referred to as single-locus methods. Multilocus methods consider joint effects of multiple genes and environmental factors. One commonly used method for family-based association analysis is implemented in FBAT. The multifactor-dimensionality reduction method (MDR) is a multilocus method, which identifies multiple genetic loci associated with the occurrence of complex disease. Many studies of late onset complex diseases employ a discordant sib pairs design. We compared the FBAT and MDR in their ability to detect susceptibility loci using a discordant sib-pair dataset generated from the simulated data made available to participants in the Genetic Analysis Workshop 14. Using FBAT, we were able to identify the effect of one susceptibility locus. However, the finding was not statistically significant. We were not able to detect any of the interactions using this method. This is probably because the FBAT test is designed to find loci with major effects, not interactions. Using MDR, the best result we obtained identified two interactions. However, neither of these reached a level of statistical significance. This is mainly due to the heterogeneity of the disease trait and noise in the data.en_US
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.rightsCopyright 2005 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.urihttp://creativecommons.org/licenses/by/2.0
dc.titleMultifactor-Dimensionality Reduction Versus Family-Based Association Tests in Detecting Susceptibility Loci in Discordant Sib-Pair Studiesen_US
dc.typearticleen_US
dc.identifier.doi10.1186/1471-2156-6-S1-S146
dc.identifier.pubmedid16451606
dc.identifier.pmcid1866789


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Copyright 2005 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 2005 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.