TY - GEN
T1 - HapMonster
T2 - 1st International Conference on Algorithms for Computational Biology, AlCoB 2014
AU - Kojima, Kaname
AU - Nariai, Naoki
AU - Mimori, Takahiro
AU - Yamaguchi-Kabata, Yumi
AU - Sato, Yukuto
AU - Kawai, Yosuke
AU - Nagasaki, Masao
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - haplotype phasing
KW - Next generation sequencing
KW - variant call
UR - http://www.scopus.com/inward/record.url?scp=84904000916&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904000916&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-07953-0_9
DO - 10.1007/978-3-319-07953-0_9
M3 - Conference contribution
AN - SCOPUS:84904000916
SN - 9783319079523
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 107
EP - 118
BT - Algorithms for Computational Biology - First International Conference, AlCoB 2014, Proceedings
PB - Springer Verlag
Y2 - 1 July 2014 through 3 July 2014
ER -