title: Penalized estimation of haplotype frequencies.
abstract: BACKGROUND
  Low haplotype diversity and linkage disequilibrium are the rule in short genomic segments. This fact suggests that parsimony should be enforced in estimation of haplotype frequencies. The current article introduces a diversity penalty that automatically discards potential haplotypes with low explanatory power. The standard EM algorithm for haplotype frequency estimation can accommodate the penalty if one passes over to a more general minorize-maximize (MM) scheme for estimation.
  
  
  RESULTS
  Our new MM algorithm converges in fewer iterations, eliminates marginal haplotypes from further consideration and reduces the computational complexity of each iteration. Estimation by the MM algorithm also improves haplotyping and genotype imputation compared to naive application of the EM algorithm. Thus, the MM algorithm is a useful substitute for the EM algorithm. Compared to the most sophisticated current methods of haplotyping and genotype imputation, the MM algorithm is slightly less accurate but at least an order of magnitude faster.
  
  
  BACKGROUND
  Our software will be made available in the next release the program Mendel at http://www.genetics.ucla.edu/software/.
authors.affiliation: Department of Biomathematics, Department of Human Genetics and Department of Statistics, University of California, Los Angeles, CA 90095, USA. kayers@ucla.edu
authors.forename: Kristin L
authors.initials: KL
authors.lastname: Ayers
authors.forename: Kenneth
authors.initials: K
authors.lastname: Lange
mesh_terms: D000465:Algorithms; D041321:Chromosomes, Human, X / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D005787:Gene Frequency; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D008297:Male; D015233:Models, Statistical; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012984:Software