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Comparison of INDEL Calling Tools with Simulation Data and Real Short-Read Data

Authors
Li, DongheKim, WonjiWang, LongfeiYoon, Kyong-AhPark, Bo youngPark, CharnyKong, Sun-YoungHwang, YongdeukBaek, DaehyunLee, Eun SookWon, Sungho
Issue Date
Sep-2019
Publisher
IEEE Computer Society
Keywords
Tools; Genomics; Data models; Cancer; Sequential analysis; Error analysis; INDEL calling; next generation sequencing; mendelian error rates
Citation
IEEE/ACM Transactions on Computational Biology and Bioinformatics, v.16, no.5, pp.1635 - 1644
Indexed
SCIE
SCOPUS
Journal Title
IEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume
16
Number
5
Start Page
1635
End Page
1644
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147142
DOI
10.1109/TCBB.2018.2854793
ISSN
1545-5963
Abstract
Insertions and deletions (INDELs) comprise a significant proportion of human genetic variation, and recent papers have revealed that many human diseases may be attributable to INDELs. With the development of next-generation sequencing (NGS) technology, many statistical/computational tools have been developed for calling INDELs. However, there are differences among those tools, and comparisons among them have been limited. In order to better understand these inter-tool differences, five popular and publicly available INDEL calling tools-GATK HaplotypeCaller, Platypus, VarScan2, Scalpel, and GotCloud-were evaluated using simulation data, 1000 Genomes Project data, and family-based sequencing data. The accuracy of INDEL calling by each tool was mainly evaluated by concordance rates. Family-based sequencing data, which consisted of 49 individuals from eight Korean families, were used to calculate Mendelian error rates. Our comparison results show that GATK HaplotypeCaller usually performs the best and that joint calling with Platypus can lead to additional improvements in accuracy. The result of this study provides important information regarding future directions for the variant detection and the algorithms development.
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