Statistical optimization of parametric accelerated failure time model for mapping survival trait loci
Most existing statistical methods for mapping quantitative trait loci (QTL) are not suitable for analyzing survival traits with a skewed distribution and censoring mechanism. As a result, researchers incorporate parametric and semi-parametric models of survival analysis into the framework of the interval mapping for QTL controlling survival traits. In survival analysis, accelerated failure time (AFT) model is considered as a de facto standard and fundamental model for data analysis. Based on AFT model, we propose a parametric approach for mapping survival traits using the EM algorithm to obtain the maximum likelihood estimates of the parameters. Also, with Bayesian information criterion (BIC) as a model selection criterion, an optimal mapping model is constructed by choosing specific error distributions with maximum likelihood and parsimonious parameters. Two real datasets were analyzed by our proposed method for illustration. The results show that among the five commonly used survival distributions, Weibull distribution is the optimal survival function for mapping of heading time in rice, while Log-logistic distribution is the optimal one for hyperoxic acute lung injury.
This preparation of work is partially supported by the National Natural Science Foundation of China (30972077) and Key Basic Research Project in Shanghai (10JC1413900). We would like to thank Dr. Annie Lin for her suggestions and helps.
- Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Spinger, New YorkGoogle Scholar
- Cox DR, Oakes D (1984) Analysis of survival data. Chapman & Hall, LondonGoogle Scholar
- Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Statist Soc B 39(1):1–38Google Scholar
- Kalbfleisch JD, Prentice RL (2002) The statistical analysis of failure time data, 2nd edn. Wiley, New YorkGoogle Scholar
- Qi JZ (2009) Comparison of proportional hazards and accelerated failure time models. Dissertation, University of SaskatchewanGoogle Scholar