ArticleBMC bioinformatics2007
Constrained hidden Markov models for population-based haplotyping.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Multiplex sequencing of plant chloroplast genomes using Solexa sequencing-by-synthesis technology.Nucleic acids research · 2008Article
- Filling the gap between biology and computer science.BioData mining · 2008Article
- Using population mixtures to optimize the utility of genomic databases: linkage disequilibrium and association study design in India.Annals of human genetics · 2008Article
- Constrained hidden Markov models for population-based haplotyping.BMC bioinformatics · 2007Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundHaplotype Reconstruction is the problem of resolving the hidden phase information in genotype data obtained from laboratory measurements. Solving this problem is an important intermediate step in gene association studies, which seek to uncover the genetic basis of complex diseases. We propose a novel approach for haplotype reconstruction based on constrained hidden Markov models. Models are constructed by incrementally refining and regularizing the structure of a simple generative model for genotype data under Hardy-Weinberg equilibrium.
resultsThe proposed method is evaluated on real-world and simulated population data. Results show that it is competitive with other recently proposed methods in terms of reconstruction accuracy, while offering a particularly good trade-off between computational costs and quality of results for large datasets.
conclusionRelatively simple probabilistic approaches for haplotype reconstruction based on structured hidden Markov models are competitive with more complex, well-established techniques in this field.
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