Mapping quantitative trait loci with censored observations.
The existing statistical methods for mapping quantitative trait loci (QTL) assume that the phenotype follows a normal distribution and is fully observed. These assumptions may not be satisfied when the phenotype pertains to the survival time or failure time, which has a skewed distribution and is usually subject to censoring due to random loss of follow-up or limited duration of the experiment. In this article, we propose an interval-mapping approach for censored failure time phenotypes. We formulate the effects of QTL on the failure time through parametric proportional hazards models and develop efficient likelihood-based inference procedures. In addition, we show how to assess genome-wide statistical significance. The performance of the proposed methods is evaluated through extensive simulation studies. An application to a mouse cross is provided.
Diao
Guoqing
G
Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599-7420, USA.
Lin
D Y
DY
Zou
Fei
F
D002874:Chromosome Mapping; D003198:Computer Simulation; D008957:Models, Genetic; D040641:Quantitative Trait Loci