A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes
Abstract
Most statistical methods for 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 there exist methods 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.
Cite
@article{arxiv.1403.3048,
title = {A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes},
author = {Il-Youp Kwak and Candace R. Moore and Edgar P. Spalding and Karl W. Broman},
journal= {arXiv preprint arXiv:1403.3048},
year = {2014}
}
Comments
Considerable changes in response to reviewers' comments. Revised the initial simulation study. Moved one figure to supplement; added another figure plus three additional supplemental figures