ArticleBMC genomics2013
V-Phaser 2: variant inference for viral populations.
Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.
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Who cites it
76 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Target capture sequencing reveals a monoclonal outbreak of respiratory syncytial virus B infections among adult hematologic patients.Antimicrobial resistance and infection control · 2022Article
- Covariation of viral recombination with single nucleotide variants during virus evolution revealed by CoVaMa.Nucleic acids research · 2022Article
- Population Variability Generated during Rescue Process and Passaging of Recombinant Mumps Viruses.Viruses · 2021Article
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- Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction.Nucleic acids research · 2021Article
- Technology dictates algorithms: recent developments in read alignment.Genome biology · 2021Review
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- Intra-Host Diversity of SARS-Cov-2 Should Not Be Neglected: Case of the State of Victoria, Australia.Viruses · 2021Article
- Epidemiological data analysis of viral quasispecies in the next-generation sequencing era.Briefings in bioinformatics · 2021Review
16 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
Abstract
backgroundMassively parallel sequencing offers the possibility of revolutionizing the study of viral populations by providing ultra deep sequencing (tens to hundreds of thousand fold coverage) of complete viral genomes. However, differentiation of true low frequency variants from sequencing errors remains challenging.
resultsWe developed a software package, V-Phaser 2, for inferring intrahost diversity within viral populations. This program adds three major new methodologies to the state of the art: a technique to efficiently utilize paired end read data for calling phased variants, a new strategy to represent and infer length polymorphisms, and an in line filter for erroneous calls arising from systematic sequencing artifacts. We have also heavily optimized memory and run time performance. This combination of algorithmic and technical advances allows V-Phaser 2 to fully utilize extremely deep paired end sequencing data (such as generated by Illumina sequencers) to accurately infer low frequency intrahost variants in viral populations in reasonable time on a standard desktop computer. V-Phaser 2 was validated and compared to both QuRe and the original V-Phaser on three datasets obtained from two viral populations: a mixture of eight known strains of West Nile Virus (WNV) sequenced on both 454 Titanium and Illumina MiSeq and a mixture of twenty-four known strains of WNV sequenced only on 454 Titanium. V-Phaser 2 outperformed the other two programs in both sensitivity and specificity while using more than five fold less time and memory.
conclusionsWe developed V-Phaser 2, a publicly available software tool (V-Phaser 2 can be accessed via: http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/v-phaser-2 and is freely available for academic use) that enables the efficient analysis of ultra-deep sequencing data produced by common next generation sequencing platforms for viral populations.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.