title: A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes.
abstract: Most statistical methods for quantitative trait loci (QTL) mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. We propose two simple, fast methods that maintain high power and precision and are amenable to extensions with multiple-QTL models using a penalized likelihood approach. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. Our methods have been implemented as a package for R, funqtl.
authors.affiliation: Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706.
authors.forename: Il-Youp
authors.initials: IY
authors.lastname: Kwak
authors.affiliation: Department of Botany, University of Wisconsin, Madison, Wisconsin 53706.
authors.forename: Candace R
authors.initials: CR
authors.lastname: Moore
authors.affiliation: Department of Botany, University of Wisconsin, Madison, Wisconsin 53706.
authors.forename: Edgar P
authors.initials: EP
authors.lastname: Spalding
authors.affiliation: Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin 53706 kbroman@biostat.wisc.edu.
authors.forename: Karl W
authors.initials: KW
authors.lastname: Broman
mesh_terms: D017360:Arabidopsis / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D016013:Likelihood Functions; D008957:Models, Genetic; D010641:Phenotype; D040641:Quantitative Trait Loci; D012044:Regression Analysis
keywords: QTL; function-valued trait; growth curves; model selection