title: Bayesian shrinkage mapping of quantitative trait loci in variance component models.
abstract: BACKGROUND
  In this article, I propose a model-selection-free method to map multiple quantitative trait loci (QTL) in variance component model, which is useful in outbred populations. The new method can estimate the variance of zero-effect QTL infinitely to zero, but nearly unbiased for non-zero-effect QTL. It is analogous to Xu's Bayesian shrinkage estimation method, but his method is based on allelic substitution model, while the new method is based on the variance component models.
  
  
  RESULTS
  Extensive simulation experiments were conducted to investigate the performance of the proposed method. The results showed that the proposed method was efficient in mapping multiple QTL simultaneously, and moreover it was more competitive than the reversible jump MCMC (RJMCMC) method and may even out-perform it.
  
  
  CONCLUSIONS
  The newly developed Bayesian shrinkage method is very efficient and powerful for mapping multiple QTL in outbred populations.
authors.affiliation: Life Science College, Heilongjiang August First Land Reclamation University, Daqing, China. fangming618@126.com
authors.forename: Ming
authors.initials: M
authors.lastname: Fang
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002874:Chromosome Mapping / Q000379:methods*; D014644:Genetic Variation; D006801:Humans; D008957:Models, Genetic; D040641:Quantitative Trait Loci