| Literature DB >> 29126106 |
Sunguk Shin1, Hanna Lee1, Hyeonju Son1,2, Soonmyung Paik1, Sangwoo Kim1.
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 ∼98% reduction of false variants when combined to conventional public pipelines and ∼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.Mesh:
Year: 2018 PMID: 29126106 DOI: 10.1093/bioinformatics/btx719
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937