title: Swift block-updating EM and pseudo-EM procedures for Bayesian shrinkage analysis of quantitative trait loci.
abstract: BACKGROUND
  Virtually all existing expectation-maximization (EM) algorithms for quantitative trait locus (QTL) mapping overlook the covariance structure of genetic effects, even though this information can help enhance the robustness of model-based inferences.
  
  
  RESULTS
  Here, we propose fast EM and pseudo-EM-based procedures for Bayesian shrinkage analysis of QTLs, designed to accommodate the posterior covariance structure of genetic effects through a block-updating scheme. That is, updating all genetic effects simultaneously through many cycles of iterations.
  
  
  CONCLUSIONS
  Simulation results based on computer-generated and real-world marker data demonstrated the ability of our method to swiftly produce sensible results regarding the phenotype-to-genotype association. Our new method provides a robust and remarkably fast alternative to full Bayesian estimation in high-dimensional models where the computational burden associated with Markov chain Monte Carlo simulation is often unwieldy. The R code used to fit the model to the data is provided in the online supplementary material.
authors: Department of Mathematics and Statistics, University of Helsinki, PO Box 68, 00014, Helsinki, Finland.
authors: Crispin M
authors: CM
authors: Mutshinda
authors: Mikko J
authors: MJ
authors: Sillanpää
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002874:Chromosome Mapping; D003198:Computer Simulation; D030541:Databases, Genetic; D005819:Genetic Markers; D001467:Hordeum / Q000235:genetics*; D008390:Markov Chains; D009010:Monte Carlo Method; D040641:Quantitative Trait Loci / Q000235:genetics*; D015203:Reproducibility of Results
chemical_list: D005819:Genetic Markers