Originally published as Genetics Published Articles Ahead of Print on April 19, 2006.

Genetics, Vol. 173, 1735-1745, July 2006, Copyright © 2006
doi:10.1534/genetics.106.055921

A Simple Linear Regression Method for Quantitative Trait Loci Linkage Analysis With Censored Observations

Carl A. Anderson*,{dagger},1, Allan F. McRae{dagger} and Peter M. Visscher*,{dagger}

* Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, Scotland EH9 3JT and {dagger} Genetic Epidemiology Group, Queensland Institute of Medical Research, Brisbane, Australia 4029

1 Corresponding author: Genetic Epidemiology Group, Queensland Institute of Medical Research, 300 Herston Rd., Brisbane, Australia 4006.
E-mail: carl.anderson{at}qimr.edu.au

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.