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A survey of current software for haplotype phase inference

In the past two years, tracking the explosion in data due to ever-improving single nucleotide polymorphism (SNP) maps and cheaper high-throughput genotyping technologies, a bewildering array of new algorithms and relevant software have appeared for haplotype phase inference. The alternatives to hapl...

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Detalles Bibliográficos
Autor principal: Weale, Michael E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525072/
https://www.ncbi.nlm.nih.gov/pubmed/15601542
http://dx.doi.org/10.1186/1479-7364-1-2-141
Descripción
Sumario:In the past two years, tracking the explosion in data due to ever-improving single nucleotide polymorphism (SNP) maps and cheaper high-throughput genotyping technologies, a bewildering array of new algorithms and relevant software have appeared for haplotype phase inference. The alternatives to haplotype inference are to resolve haplotypes completely, either by in vitro methods or by typing close pedigrees, which is expensive and is not guaranteed in pedigrees, or to ignore haplotype-level analysis in favour of genotype-level analysis, which avoids the danger of treating inferred haplotypes as real but denies the researcher, potentially, any valuable analytic insights. This review attempts a snapshot of this rapidly moving field as it stands at present, and is mainly restricted, given the current predominance of SNP genotyping, to the consideration of diallelic data. For completeness, the review will occasionally refer to algorithms for which no software exists.