A nonlinear mixed-effect mixture model for functional mapping of dynamic traits.
Functional mapping has emerged as a next-generation statistical tool for mapping quantitative trait loci (QTL) that affect complex dynamic traits. In this article, we incorporated the idea of nonlinear mixed-effect (NLME) models into the mixture-based framework of functional mapping, aimed to generalize the spectrum of applications for functional mapping. NLME-based functional mapping, implemented with the linearization algorithm based on the first-order Taylor expansion, can provide reasonable estimates of QTL genotypic-specific curve parameters (fixed effect) and the between-individual variation of these parameters (random effect). Results from simulation studies suggest that the NLME-based model is more general than traditional functional mapping. The new model can be useful for the identification of the ontogenetic patterns of QTL genetic effects during time course.
Hou
W
W
Department of Statistics, University of Florida, Gainesville, FL 32611, USA.
Li
H
H
Zhang
B
B
Huang
M
M
Wu
R
R
D000465:Algorithms; D003198:Computer Simulation; D005838:Genotype; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D010641:Phenotype; D032107:Populus / Q000235:genetics*; D019655:Quantitative Trait, Heritable