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dc.contributor.authorWilcox, Marsha A.en_US
dc.contributor.authorWyszynski, Diego F.en_US
dc.contributor.authorPanhuysen, Carolien I.en_US
dc.contributor.authorMa, Qianlien_US
dc.contributor.authorYip, Agustinen_US
dc.contributor.authorFarrell, Johnen_US
dc.contributor.authorFarrer, Lindsay A.en_US
dc.date.accessioned2012-01-09T20:53:14Z
dc.date.available2012-01-09T20:53:14Z
dc.date.copyright2003
dc.date.issued2003-12-31
dc.identifier.citationWilcox, Marsha A, Diego F Wyszynski, Carolien I Panhuysen, Qianli Ma, Agustin Yip, John Farrell, Lindsay A Farrer. "Empirically derived phenotypic subgroups – qualitative and quantitative trait analyses" BMC Genetics 4(Suppl 1):S15. (2003)
dc.identifier.issn1471-2156
dc.identifier.urihttp://hdl.handle.net/2144/2891
dc.description.abstractBACKGROUND. The Framingham Heart Study has contributed a great deal to advances in medicine. Most of the phenotypes investigated have been univariate traits (quantitative or qualitative). The aims of this study are to derive multivariate traits by identifying homogeneous groups of people and assigning both qualitative and quantitative trait scores; to assess the heritability of the derived traits; and to conduct both qualitative and quantitative linkage analysis on one of the heritable traits. METHODS. Multiple correspondence analysis, a nonparametric analogue of principal components analysis, was used for data reduction. Two-stage clustering, using both k-means and agglomerative hierarchical clustering, was used to cluster individuals based upon axes (factor) scores obtained from the data reduction. Probability of cluster membership was calculated using binary logistic regression. Heritability was calculated using SOLAR, which was also used for the quantitative trait analysis. GENEHUNTER-PLUS was used for the qualitative trait analysis. RESULTS. We found four phenotypically distinct groups. Membership in the smallest group was heritable (38%, p < 1 × 10-6) and had characteristics consistent with atherogenic dyslipidemia. We found both qualitative and quantitative LOD scores above 3 on chromosomes 11 and 14 (11q13, 14q23, 14q31). There were two Kong & Cox LOD scores above 1.0 on chromosome 6 (6p21) and chromosome 11 (11q23). CONCLUSION. This approach may be useful for the identification of genetic heterogeneity in complex phenotypes by clarifying the phenotype definition prior to linkage analysis. Some of our findings are in regions linked to elements of atherogenic dyslipidemia and related diagnoses, some may be novel, or may be false positives.en_US
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.rightsCopyright 2003 Wilcox 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.titleEmpirically Derived Phenotypic Subgroups – Qualitative and Quantitative Trait Analysesen_US
dc.typearticleen_US
dc.identifier.doi10.1186/1471-2156-4-S1-S15
dc.identifier.pubmedid14975083
dc.identifier.pmcid1866449


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Copyright 2003 Wilcox 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 2003 Wilcox 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.