A nonlinear mixed-effect mixture model for functional mapping of dynamic traits

W. Hou, H. Li, B. Zhang, M. Huang, R. Wu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)321-328
Number of pages8
Issue number4
StatePublished - Oct 2008

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)


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