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AIRVF: a filtering toolbox for precise variant calling in Ion Torrent sequencing

Authors
 Sunguk Shin  ;  Hanna Lee  ;  Hyeonju Son  ;  Soonmyung Paik  ;  Sangwoo Kim 
Citation
 Bioinfomatics, Vol.34(7) : 1232-1234, 2018 
Journal Title
 Bioinfomatics 
ISSN
 1367-4803 
Issue Date
2018
Abstract
Summary: Ion Torrent sequencing is one of the most frequently used platforms in healthcare research and industry. Despite many advantages, platform-specific artifacts complicate efficient separation of true variants from errors, especially in variants with lower allele frequencies (<15%). Here, we developed a multi-step filtering toolbox AIRVF that works on flowgram, raw and mapped reads and called variants to reduce artifact-driven false variant calls. Tests on sequencing data of standard reference material showed up to approximately 98% reduction of false variants when combined to conventional public pipelines and approximately 48% to the in-house commercial solution, with a minimal loss of sensitivity. Availability and implementation: The program with a detailed manual is available at https://sourceforge.net/projects/airvf/. Contact: swkim@yuhs.ac. Supplementary information: Supplementary data are available at Bioinformatics online.
Full Text
https://academic.oup.com/bioinformatics/article/34/7/1232/4596945
DOI
10.1093/bioinformatics/btx719
Appears in Collections:
1. Journal Papers (연구논문) > 1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부)
1. Journal Papers (연구논문) > 1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원)
Yonsei Authors
김상우(Kim, Sangwoo)
백순명(Paik, Soon Myung) ORCID logo https://orcid.org/0000-0001-9688-6480
이한나(Lee, Hanna)
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URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/162185
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