Grouping preprocess for haplotype inference from SNP and CNV data

Hiroyuki Shindo, Hiroshi Chigira, Tomoyo Nagaoka, Naoyuki Kamatani, Masato Inoue

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    The method of statistical haplotype inference is an indispensable technique in the field of medical science. The authors previously reported Hardy-Weinberg equilibrium-based haplotype inference that could manage single nucleotide polymorphism (SNP) data. We recently extended the method to cover copy number variation (CNV) data. Haplotype inference from mixed data is important because SNPs and CNVs are occasionally in linkage disequilibrium. The idea underlying the proposed method is simple, but the algorithm for it needs to be quite elaborate to reduce the calculation cost. Consequently, we have focused on the details on the algorithm in this study. Although the main advantage of the method is accuracy, in that it does not use any approximation, its main disadvantage is still the calculation cost, which is sometimes intractable for large data sets with missing values.

    Original languageEnglish
    Article number012009
    JournalJournal of Physics: Conference Series
    Volume197
    DOIs
    Publication statusPublished - 2009

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    polymorphism
    nucleotides
    inference
    medical science
    costs
    linkages
    approximation

    ASJC Scopus subject areas

    • Physics and Astronomy(all)

    Cite this

    Grouping preprocess for haplotype inference from SNP and CNV data. / Shindo, Hiroyuki; Chigira, Hiroshi; Nagaoka, Tomoyo; Kamatani, Naoyuki; Inoue, Masato.

    In: Journal of Physics: Conference Series, Vol. 197, 012009, 2009.

    Research output: Contribution to journalArticle

    Shindo, Hiroyuki ; Chigira, Hiroshi ; Nagaoka, Tomoyo ; Kamatani, Naoyuki ; Inoue, Masato. / Grouping preprocess for haplotype inference from SNP and CNV data. In: Journal of Physics: Conference Series. 2009 ; Vol. 197.
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