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Genetics. 2014 Aug;197(4):1409-16. doi: 10.1534/genetics.114.166306. Epub 2014 Jun 14.

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

Author information

1
Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706.
2
Department of Botany, University of Wisconsin, Madison, Wisconsin 53706.
3
Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin 53706 kbroman@biostat.wisc.edu.

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.

KEYWORDS:

QTL; function-valued trait; growth curves; model selection

PMID:
24931408
PMCID:
PMC4125409
DOI:
10.1534/genetics.114.166306
[Indexed for MEDLINE]
Free PMC Article
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