Literature DB >> 11793729

Locating the genes underlying a simulated complex disease by discriminant analysis.

X Li1, S Rao, R C Elston, J M Olson, K L Moser, T Zhang, Z Guo.   

Abstract

The purpose of this study was to propose and evaluate a novel multivariate approach for genetic mapping of complex binary human diseases. This approach uses the application of either of two methods of standard (stepwise) discriminant analysis to detect linkage based on the differential marker identity-by-descent distributions among the three affection groups of sib pairs (concordantly affected, discordant, and concordantly unaffected). One of the advantages of this approach is that it allows for simultaneously testing all markers, as well as other genetic and environmental factors, in a single multivariate setting. We have explored its properties and behaviors via an application to the simulated data in Genetic Analysis Workshop 12.

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Mesh:

Year:  2001        PMID: 11793729     DOI: 10.1002/gepi.2001.21.s1.s516

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  3 in total

1.  Generalized T2 test for genome association studies.

Authors:  Momiao Xiong; Jinying Zhao; Eric Boerwinkle
Journal:  Am J Hum Genet       Date:  2002-03-29       Impact factor: 11.025

2.  Multivariate sib-pair linkage analysis of longitudinal phenotypes by three step-wise analysis approaches.

Authors:  Zheng Guo; Xia Li; Shaoqi Rao; Kathy L Moser; Tianwen Zhang; Binsheng Gong; Gongqing Shen; Lin Li; Ruth Cannata; Erich Zirzow; Eric J Topol; Qing Wang
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

3.  Analysis of heterogeneity and epistasis in physiological mixed populations by combined structural equation modelling and latent class analysis.

Authors:  Mogens Fenger; Allan Linneberg; Thomas Werge; Torben Jørgensen
Journal:  BMC Genet       Date:  2008-07-08       Impact factor: 2.797

  3 in total

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