Journal of Agricultural, Biological, and Environmental Statistics

, 12:300

Incorporating LASSO effects into a mixed model for quantitative trait loci detection

Authors

    • School of Agriculture, Food and WineThe University of Adelaide
  • Arūnas P. Verbyla
    • School of Agriculture, Food and WineThe University of Adelaide
  • Wayne S. Pitchford
    • School of Agriculture, Food and WineThe University of Adelaide
Article

DOI: 10.1198/108571107X200396

Cite this article as:
Foster, S.D., Verbyla, A.P. & Pitchford, W.S. JABES (2007) 12: 300. doi:10.1198/108571107X200396

Abstract

The identification of quantitative trait loci (QTL) can be viewed as a subset selection problem. In a simulation study the least absolute selection and shrinkage operator (LASSO) is shown to be a useful and powerful tool for QTL identification. LASSO effects are embedded into a mixed model allowing simultaneous modeling of genetic and experimental effects. This provides the flexibility to model the experiment in conjunction with the power of LASSO QTL identification. Estimation is performed using an approximation to the restricted likelihood and modified Gaussian elimination. The extended mixed model is used to analyze a cattle gene mapping dataset.

Key Words

Adjusted scoresPartial Laplace approximationQuantitative trial lociRestricted likelihoodSubset selection

Copyright information

© International Biometric Society 2007