A maximum likelihood approach to functional mapping of longitudinal binary traits

Chenguang Wang, Hongying Li, Zhong Wang, Yaqun Wang, Ningtao Wang, Zuoheng Wang, Rongling Wu

Research output: Contribution to journalArticlepeer-review


Despite their importance in biology and biomedicine, genetic mapping of binary traits that change over time has not been well explored. In this article, we develop a statistical model for mapping quantitative trait loci (QTLs) that govern longitudinal responses of binary traits. The model is constructed within the maximum likelihood framework by which the association between binary responses is modeled in terms of conditional log odds-ratios. With this parameterization, the maximum likelihood estimates (MLEs) of marginal mean parameters are robust to the misspecification of time dependence. We implement an iterative procedures to obtain the MLEs of QTL genotype-specific parameters that define longitudinal binary responses. The usefulness of the model was validated by analyzing a real example in rice. Simulation studies were performed to investigate the statistical properties of the model, showing that the model has power to identify and map specific QTLs responsible for the temporal pattern of binary traits.

Original languageEnglish (US)
Article number2
JournalStatistical Applications in Genetics and Molecular Biology
Issue number6
StatePublished - Nov 2012

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Molecular Biology
  • Genetics
  • Computational Mathematics


Dive into the research topics of 'A maximum likelihood approach to functional mapping of longitudinal binary traits'. Together they form a unique fingerprint.

Cite this