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Most statistical methods for QTL mapping focus on a single phenotype.However, multiple phenotypes are commonly measured, and recent technologicaladvances have greatly simplified the automated acquisition of numerousphenotypes, including function-valued phenotypes, such as growth measured overtime. While there exist methods for QTL mapping with function-valuedphenotypes, they are generally computationally intensive and focus onsingle-QTL models. We propose two simple, fast methods that maintain high powerand precision and are amenable to extensions with multiple-QTL models using apenalized likelihood approach. After identifying multiple QTL by theseapproaches, we can view the function-valued QTL effects to provide a deeperunderstanding of the underlying processes. Our methods have been implemented asa package for R, funqtl.

A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes