Genetic mapping of complex traits by minimizing integrated square errors

BMC Genetics

Research Article

Rongling Wu¹  Zhong Wang¹  Guifang Fu²  Song Wu³  Yunmei Chen⁴ 

[1] Center for Computational Biology, Beijing Forestry University, 100083, Beijing, China;Center for Statistical Genetics, Pennsylvania State University, 17033, Hershey, PA, USA;Center for Statistical Genetics, Pennsylvania State University, 17033, Hershey, PA, USA;Department of Applied Mathematics and Statistics, the State University of New York at Stony Brook, 11790, Stony Brook, NY, USA;Center for Computational Biology, Beijing Forestry University, 100083, Beijing, China;Department of Mathematics, University of Florida, 32611, Gainesville, FL, USA;

关键词: Energy Function;    Marker Genotype;    Marker Position;    Error Density;    Body Mass Data;   

DOI  :  10.1186/1471-2156-13-20

 received in 2011-06-02, accepted in 2012-03-23,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundGenetic mapping has been used as a tool to study the genetic architecture of complex traits by localizing their underlying quantitative trait loci (QTLs). Statistical methods for genetic mapping rely on a key assumption, that is, traits obey a parametric distribution. However, in practice real data may not perfectly follow the specified distribution.ResultsHere, we derive a robust statistical approach for QTL mapping that accommodates a certain degree of misspecification of the true model by incorporating integrated square errors into the genetic mapping framework. A hypothesis testing is formulated by defining a new test statistics - energy difference.ConclusionsSimulation studies were performed to investigate the statistical properties of this approach and compare these properties with those from traditional maximum likelihood and non-parametric QTL mapping approaches. Lastly, analyses of real examples were conducted to demonstrate the usefulness and utilization of the new approach in a practical genetic setting.

【 授权许可】

CC BY   
© Wu et al; licensee BioMed Central Ltd. 2012