HapMonster: A statistically unified approach for variant calling and haplotyping based on phase-informative reads

Kaname Kojima, Naoki Nariai, Takahiro Mimori, Yumi Yamaguchi-Kabata, Yukuto Sato, Yosuke Kawai, Masao Nagasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Haplotype phasing is essential for identifying disease-causing variants with phase-dependent interactions as well as for the coalescent-based inference of demographic history. One of approaches for estimating haplotypes is to use phase-informative reads, which span multiple heterozygous variant positions. Although the quality of estimated variants is crucial in haplotype phasing, accurate variant calling is still challenging due to errors on sequencing and read mapping. Since some of such errors can be corrected by considering haplotype phasing, simultaneous estimation of variants and haplotypes is important. Thus, we propose a statistically unified approach for variant calling and haplotype phasing named HapMonster, where haplotype phasing information is used for improving the accuracy of variant calling and the improved variant calls are used for more accurate haplotype phasing. From the comparison with other existing methods on simulation and real sequencing data, we confirm the effectiveness of HapMonster in both variant calling and haplotype phasing.

Original languageEnglish
Title of host publicationAlgorithms for Computational Biology - First International Conference, AlCoB 2014, Proceedings
PublisherSpringer-Verlag
Pages107-118
Number of pages12
ISBN (Print)9783319079523
DOIs
Publication statusPublished - 2014 Jan 1
Event1st International Conference on Algorithms for Computational Biology, AlCoB 2014 - Tarragona, Spain
Duration: 2014 Jul 12014 Jul 3

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8542 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Conference on Algorithms for Computational Biology, AlCoB 2014
CountrySpain
CityTarragona
Period14/7/114/7/3

Keywords

  • Next generation sequencing
  • haplotype phasing
  • variant call

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Kojima, K., Nariai, N., Mimori, T., Yamaguchi-Kabata, Y., Sato, Y., Kawai, Y., & Nagasaki, M. (2014). HapMonster: A statistically unified approach for variant calling and haplotyping based on phase-informative reads. In Algorithms for Computational Biology - First International Conference, AlCoB 2014, Proceedings (pp. 107-118). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8542 LNBI). Springer-Verlag. https://doi.org/10.1007/978-3-319-07953-0_9