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Parameter estimation and quantitative parametric linkage analysis with GENEHUNTER-QMOD.
Hum. Hered. 73, 208-219 (2012)
Objective: We present a parametric method for linkage analysis of quantitative phenotypes. The method provides a test for linkage as well as an estimate of different phenotype parameters. We have implemented our new method in the program GENEHUNTER-QMOD and evaluated its properties by performing simulations. Methods: The phenotype is modeled as a normally distributed variable, with a separate distribution for each genotype. Parameter estimates are obtained by maximizing the LOD score over the normal distribution parameters with a gradient-based optimization called PGRAD method. Results: The PGRAD method has lower power to detect linkage than the variance components analysis (VCA) in case of a normal distribution and small pedigrees. However, it outperforms the VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data and non-normally distributed phenotypes. Here, the higher power even goes along with conservativeness, while the VCA has an inflated type I error. Parameter estimation tends to underestimate residual variances but performs better for expectation values of the phenotype distributions. Conclusion: With GENEHUNTER-QMOD, a powerful new tool is provided to explicitly model quantitative phenotypes in the context of linkage analysis. It is freely available at http://www.helmholtz-muenchen.de/genepi/downloads.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Linkage Analysis ; Likelihood Calculation ; Quantitative Phenotypes ; Multipoint Analysis ; Lander-green Algorithm ; Genehunter; MITE SENSITIZATION; GENERAL PEDIGREES; SCORE ANALYSIS; MARKER LOCUS; LOD SCORES; TRAIT; TESTS; OPTIMIZATION; MODSCORE; GENETICS
ISSN (print) / ISBN
0001-5652
e-ISSN
1423-0062
Journal
Human Heredity
Quellenangaben
Volume: 73,
Issue: 4,
Pages: 208-219
Publisher
Karger
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Genetic Epidemiology (IGE)