Haplotype inference via hierarchical genotype parsing

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Abstract

The within-species genetic variation due to recombinations leads to a mosaic-like structure of DNA. This structure can be modeled, e.g. by parsing sample sequences of current DNA with respect to a small number of founders. The founders represent the ancestral sequence material from which the sample was created in a sequence of recombination steps. This scenario has recently been successfully applied on developing probabilistic Hidden Markov Methods for haplotyping genotypic data. In this paper we introduce a combinatorial method for haplotyping that is based on a similar parsing idea. We formulate a polynomial-time parsing algorithm that finds minimum cross-over parse in a simplified 'flat' parsing model that ignores the historical hierarchy of recombinations. The problem of constructing optimal founders that would give minimum possible parse for given genotypic sequences is shown NP-hard. A heuristic locally-optimal algorithm is given for founder construction. Combined with flat parsing this already gives quite good haplotyping results. Improved haplotyping is obtained by using a hierarchical parsing that properly models the natural recombination process. For finding short hierarchical parses a greedy polynomial-time algorithm is given. Empirical haplotyping results on HapMap data are reported. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Rastas, P., & Ukkonen, E. (2007). Haplotype inference via hierarchical genotype parsing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4645 LNBI, pp. 85–97). Springer Verlag. https://doi.org/10.1007/978-3-540-74126-8_9

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