Document Detail


Statistical optimization of parametric accelerated failure time model for mapping survival trait loci.
MedLine Citation:
PMID:  21107519     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Zhongze Piao; Xiaojing Zhou; Li Yan; Ying Guo; Runqing Yang; Zhixiang Luo; Daniel R Prows
Related Documents :
21428999 - A phase transition model for the speed-accuracy trade-off in response time experiments.
21108009 - A novel direct equipartition ray design (equray) procedure for toxicity interaction bet...
23720249 - A virtual training system for maxillofacial surgery using advanced haptic feedback and ...
21463859 - Automated detection of the osseous acetabular rim using three-dimensional models of the...
9395389 - Radar detection of the nucleus and coma of comet hyakutake
20414699 - Rapid prediction of solvation free energy. 3. application to the sampl2 challenge.
23494809 - Robust bayesian inference for multivariate longitudinal data by using normal/independen...
25046019 - Improved artificial bee colony algorithm based gravity matching navigation method.
24124789 - Psychometric properties of the dyadic adjustment scale (das) in a community sample of c...
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-11-25
Journal Detail:
Title:  TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik     Volume:  122     ISSN:  1432-2242     ISO Abbreviation:  Theor. Appl. Genet.     Publication Date:  2011 Mar 
Date Detail:
Created Date:  2011-02-22     Completed Date:  2011-06-09     Revised Date:  2014-09-18    
Medline Journal Info:
Nlm Unique ID:  0145600     Medline TA:  Theor Appl Genet     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  855-63     Citation Subset:  IM    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Acute Lung Injury / genetics
Algorithms
Animals
Bayes Theorem
Chromosome Mapping*
Female
Likelihood Functions
Male
Mice
Mice, Inbred C57BL
Models, Genetic*
Models, Statistical*
Oryza sativa / genetics
Phenotype
Quantitative Trait Loci*
Survival Analysis
Grant Support
ID/Acronym/Agency:
R01 HL075562/HL/NHLBI NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Functional markers developed from multiple loci in GS3 for fine marker-assisted selection of grain l...
Next Document:  Dissociation of lipotoxicity and glucotoxicity in a mouse model of obesity associated diabetes: role...