VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering | Zendy

Bie Verbist | Zendy; Kim Thys | Zendy; Joke Reumers | Zendy; Yves Wetzels | Zendy; Koen Van der Borght | Zendy; Willem Talloen | Zendy; Jeroen Aerssens | Zendy; Lieven Clement | Zendy; Olivier Thas | Zendy

Open Access

VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering

Author(s) -

Bie Verbist,

Kim Thys,

Joke Reumers,

Yves Wetzels,

Koen Van der Borght,

Willem Talloen,

Jeroen Aerssens,

Lieven Clement,

Olivier Thas

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu587

Subject(s) - massive parallel sequencing , illumina dye sequencing , pipeline (software) , computational biology , genetics , biology , computer science , deep sequencing , mutation , dna sequencing , data mining , genome , gene , programming language

In virology, massively parallel sequencing (MPS) opens many opportunities for studying viral quasi-species, e.g. in HIV-1- and HCV-infected patients. This is essential for understanding pathways to resistance, which can substantially improve treatment. Although MPS platforms allow in-depth characterization of sequence variation, their measurements still involve substantial technical noise. For Illumina sequencing, single base substitutions are the main error source and impede powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores (Qs) that are useful for differentiating errors from the real low-frequency mutations.

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