ArticleBioinformatics (Oxford, England)2009
Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Isomorphism and similarity for 2-generation pedigrees.BMC bioinformatics · 2015Article
- Haplotypes versus genotypes on pedigrees.Algorithms for molecular biology : AMB · 2011Article
- A genetic algorithm-based Boolean delay model of intracellular signal transduction in inflammation.BMC bioinformatics · 2011Article
- Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping.Bioinformatics (Oxford, England) · 2010Article
- Efficient identification of identical-by-descent status in pedigrees with many untyped individuals.Bioinformatics (Oxford, England) · 2010Article
- Efficient genome ancestry inference in complex pedigrees with inbreeding.Bioinformatics (Oxford, England) · 2010Article
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3 authors.
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Abstract
unlabelledWe develop an hidden Markov model (HMM)-based algorithm for computing exact parametric and non-parametric linkage scores in larger pedigrees than was possible before. The algorithm is applicable whenever there are chains of persons in the pedigree with no genetic measurements and with unknown affection status. The algorithm is based on shrinking the state space of the HMM considerably using such chains. In a two g-degree cousins pedigree the reduction drops the state space from being exponential in g to being linear in g. For a Finnish family in which two affected children suffer from a rare cold-inducing sweating syndrome, we were able to reduce the state space by more than five orders of magnitude from 2(50) to 2(32). In another pedigree of state-space size of 2(27), used for a study of pituitary adenoma, the state space reduced by a factor of 8.5 and consequently exact linkage scores can now be computed, rather than approximated. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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