Literature DB >> 29126106

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

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


  1 in total

1.  Identification of single nucleotide variants using position-specific error estimation in deep sequencing data.

Authors:  Dimitrios Kleftogiannis; Marco Punta; Anuradha Jayaram; Shahneen Sandhu; Stephen Q Wong; Delila Gasi Tandefelt; Vincenza Conteduca; Daniel Wetterskog; Gerhardt Attard; Stefano Lise
Journal:  BMC Med Genomics       Date:  2019-08-02       Impact factor: 3.063

  1 in total

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