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How frugal is mother nature with haplotypes?
School of Medicine, Washington University, United States.
Computer Science Institute, University of Halle-Wittenberg, Germany.
Department of Biology, Washington University, United States.
Department of Computer Science/Department of Genetics, Washington University, United States.
2009 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 25, no 1, 68-74 p.Article in journal (Refereed) Published
Abstract [en]

Motivation: Inference of haplotypes from genotype data is crucial and challenging for many vitally important studies. The first, and most critical step, is the ascertainment of a biologically sound model to be optimized. Many models that have been proposed rely partially or entirely on reducing the number of unique haplotypes in the solution.

Results: This article examines the parsimony of haplotypes using known haplotypes as well as genotypes from the HapMap project. Our study reveals that there are relatively few unique haplotypes, but not always the least possible, for the datasets with known solutions. Furthermore, we show that there are frequently very large numbers of parsimonious solutions, and the number increases exponentially with increasing cardinality. Moreover, these solutions are quite varied, most of which are not consistent with the true solutions. These results quantify the limitations of the Pure Parsimony model and demonstrate the imperative need to consider additional properties for haplotype inference models. At a higher level, and with broad applicability, this article illustrates the power of combinatorial methods to tease out imperfections in a given biological model.

Place, publisher, year, edition, pages
Oxford: Oxford University Press, 2009. Vol. 25, no 1, 68-74 p.
Keyword [en]
pure parsimony, maximum parsimony, human genome, inference, populations, algorithms, map
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:umu:diva-100103DOI: 10.1093/bioinformatics/btn572ISI: 000261996400011OAI: oai:DiVA.org:umu-100103DiVA: diva2:790209
Available from: 2015-02-23 Created: 2015-02-23 Last updated: 2017-12-04Bibliographically approved

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