Grouping preprocess for haplotype inference from SNP and CNV data

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

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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 Jan 1

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ASJC Scopus subject areas

  • Physics and Astronomy(all)

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