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Bioinformatics Advance Access originally published online on May 16, 2008
Bioinformatics 2008 24(14):1596-1602; doi:10.1093/bioinformatics/btn236
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Penalized estimation of haplotype frequencies

Kristin L. Ayers 1,* and Kenneth Lange 1,2,3,*

1Department of Biomathematics, 2Department of Human Genetics and 3Department of Statistics, University of California, Los Angeles, CA 90095, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: 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.

Availability: Our software will be made available in the next release the program Mendel at http://www.genetics.ucla.edu/software/.

Contact: kayers{at}ucla.edu

Associate Editor: Martin Bishop

Received on March 29, 2008; revised on May 13, 2008; accepted on May 14, 2008

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