SpeedHap: an accurate heuristic for the single individual SNP haplotyping problem with many gaps, high reading error rate and low coverage.
Identifieur interne : 000607 ( Ncbi/Checkpoint ); précédent : 000606; suivant : 000608SpeedHap: an accurate heuristic for the single individual SNP haplotyping problem with many gaps, high reading error rate and low coverage.
Auteurs : Loredana M. Genovese [Italie] ; Filippo Geraci ; Marco PellegriniSource :
- IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM [ 1557-9964 ]
Descripteurs français
- KwdFr :
- Algorithmes, Analyse de mutations d'ADN (), Analyse de séquence d'ADN (), Cartographie chromosomique (), Données de séquences moléculaires, Haplotypes (génétique), Humains, Logiciel, Polymorphisme de nucléotide simple (génétique), Reproductibilité des résultats, Sensibilité et spécificité, Séquence nucléotidique.
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
Single nucleotide polymorphism (SNP) is the most frequent form of DNA variation. The set of SNP's present in a chromosome (called the haplotype) is of interest in a wide area of applications in molecular biology and biomedicine, including diagnostic and medical therapy. In this paper we propose a new heuristic method for the problem of haplotype reconstruction for (portions of) a pair of homologous human chromosomes from a single individual (SIH). The problem is well known in literature and exact algorithms have been proposed for the case when no (or few) gaps are allowed in the input fragments. These algorithms, though exact and of polynomial complexity, are slow in practice. When gaps are considered no exact method of polynomial complexity is known. The problem is also hard to approximate with guarantees. Therefore fast heuristics have been proposed. In this paper we describe SpeedHap, a new heuristic method that is able to tackle the case of many gapped fragments and retains its effectiveness even when the input fragments have high rate of reading errors (up to 20%) and low coverage (as low as 3). We test SpeedHap on real data from the HapMap Project.
DOI: 10.1109/TCBB.2008.67
PubMed: 18989037
Affiliations:
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pubmed:18989037Le document en format XML
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<term>Logiciel</term>
<term>Reproductibilité des résultats</term>
<term>Sensibilité et spécificité</term>
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<front><div type="abstract" xml:lang="en">Single nucleotide polymorphism (SNP) is the most frequent form of DNA variation. The set of SNP's present in a chromosome (called the haplotype) is of interest in a wide area of applications in molecular biology and biomedicine, including diagnostic and medical therapy. In this paper we propose a new heuristic method for the problem of haplotype reconstruction for (portions of) a pair of homologous human chromosomes from a single individual (SIH). The problem is well known in literature and exact algorithms have been proposed for the case when no (or few) gaps are allowed in the input fragments. These algorithms, though exact and of polynomial complexity, are slow in practice. When gaps are considered no exact method of polynomial complexity is known. The problem is also hard to approximate with guarantees. Therefore fast heuristics have been proposed. In this paper we describe SpeedHap, a new heuristic method that is able to tackle the case of many gapped fragments and retains its effectiveness even when the input fragments have high rate of reading errors (up to 20%) and low coverage (as low as 3). We test SpeedHap on real data from the HapMap Project.</div>
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