ViQuaS | Datasets2Tools

General Information

Description	An improved reconstruction pipeline for viral quasispecies spectra generated by next-generation sequencing
Homepage	http://sourceforge.net/projects/viquas/

Publications

Bioinformatics (2014)

ViQuaS: an improved reconstruction pipeline for viral quasispecies spectra generated by next-generation sequencing

Duleepa Jayasundara; I. Saeed; Suhinthan Maheswararajah; B.C. Chang; S.-L. Tang; Saman K. Halgamuge

Motivation: The combined effect of a high replication rate and the low fidelity of the viral polymerase in most RNA viruses and some DNA viruses results in the formation of a viral quasispecies. Uncovering information about quasispecies populations significantly benefits the study of disease progression, antiviral drug design, vaccine design and viral pathogenesis. We present a new analysis pipeline called ViQuaS for viral quasispecies spectrum reconstruction using short next-generation sequencing reads. ViQuaS is based on a novel reference-assisted de novo assembly algorithm for constructing local haplotypes. A significantly extended version of an existing global strain reconstruction algorithm is also used.

Results: Benchmarking results showed that ViQuaS outperformed three other previously published methods named ShoRAH, QuRe and PredictHaplo, with improvements of at least 3.1–53.9% in recall, 0–12.1% in precision and 0–38.2% in F-score in terms of strain sequence assembly and improvements of at least 0.006–0.143 in KL-divergence and 0.001–0.035 in root mean-squared error in terms of strain frequency estimation, over the next-best algorithm under various simulation settings. We also applied ViQuaS on a real read set derived from an in vitro human immunodeficiency virus (HIV)-1 population, two independent datasets of foot-and-mouth-disease virus derived from the same biological sample and a real HIV-1 dataset and demonstrated better results than other methods available.

Availability and implementation: http://sourceforge.net/projects/viquas/

Contact: d.jayasundara@student.unimelb.edu.au

Supplementary information: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btu754

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