ViCTree: an automated framework for taxonomic classification from protein sequences

Modha, Sejal; Thanki, Anil; Cotmore, Susan F.; Davison, Andrew J.; Hughes, Joseph

doi:10.1093/bioinformatics/bty099

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…The classification of such a diverse set of organisms constitutes a challenging task and is impossible to accomplish within reasonable time using phenotypic characters. Quantitative computational methods could provide a viable alternative, particularly for large scale clustering and fast identification of viral strains (Simmonds et al, 2017; Modha et al, 2018). Using empirical data of the HBV and HCV viruses we show that by applying phylogeny-aware and distance-based tools to classify the strains of the two virus types, the corresponding genetic clustering closely recovers their currently accepted taxonomy.…”

Section: Resultsmentioning

confidence: 99%

“…The additional assumption of mPTP, that the genetic variation may differ substantially among species allows to accurately delimit species in large (meta-) barcoding datasets comprising multiple species of diverse life histories (Kapli et al, 2017). Experiments using empirical data for several animal phyla (Kapli et al, 2017) and recently also viruses (Thézé et al, 2018; Modha et al, 2018) show that the method consistently provides extremely fast and sensible species estimates on ‘classic’ phylogenetic marker and barcoding genes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automated, phylogeny-based genotype delimitation of the Hepatitis Viruses HBV and HCV

Serdari

Kostaki

Paraskevis

et al. 2019

PeerJ

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BackgroundThe classification of hepatitis viruses still predominantly relies on ad hoc criteria, i.e., phenotypic traits and arbitrary genetic distance thresholds. Given the subjectivity of such practices coupled with the constant sequencing of samples and discovery of new strains, this manual approach to virus classification becomes cumbersome and impossible to generalize.MethodsUsing two well-studied hepatitis virus datasets, HBV and HCV, we assess if computational methods for molecular species delimitation that are typically applied to barcoding biodiversity studies can also be successfully deployed for hepatitis virus classification. For comparison, we also used ABGD, a tool that in contrast to other distance methods attempts to automatically identify the barcoding gap using pairwise genetic distances for a set of aligned input sequences.Results—DiscussionWe found that the mPTP species delimitation tool identified even without adapting its default parameters taxonomic clusters that either correspond to the currently acknowledged genotypes or to known subdivision of genotypes (subtypes or subgenotypes). In the cases where the delimited cluster corresponded to subtype or subgenotype, there were previous concerns that their status may be underestimated. The clusters obtained from the ABGD analysis differed depending on the parameters used. However, under certain values the results were very similar to the taxonomy and mPTP which indicates the usefulness of distance based methods in virus taxonomy under appropriate parameter settings. The overlap of predicted clusters with taxonomically acknowledged genotypes implies that virus classification can be successfully automated.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated, phylogeny-based genotype delimitation of the Hepatitis Viruses HBV and HCV

Serdari

Kostaki

Paraskevis

et al. 2019

PeerJ

View full text Add to dashboard Cite

show abstract

“…This will undoubtedly pose challenges to the taxonomic classification of viruses, which often needs expert knowledge and skills to submit classification proposals to the ICTV. Automated metagenomic pipelines such as MetaViC and virus sequence classification tools such as ViCTree [61] will help to streamline some of the steps involved in virus classification. In the current version of the MetaViC pipeline, a further sequence assembly tool such as digital normalisation could be added.…”

Section: Discussionmentioning

confidence: 99%

Metaviromics Reveals Unknown Viral Diversity in the Biting Midge Culicoides impunctatus

Modha

Hughes

Bianco

et al. 2019

Viruses

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Biting midges (Culicoides species) are vectors of arboviruses and were responsible for the emergence and spread of Schmallenberg virus (SBV) in Europe in 2011 and are likely to be involved in the emergence of other arboviruses in Europe. Improved surveillance and better understanding of risks require a better understanding of the circulating viral diversity in these biting insects. In this study, we expand the sequence space of RNA viruses by identifying a number of novel RNA viruses from Culicoides impunctatus (biting midge) using a meta-transcriptomic approach. A novel metaviromic pipeline called MetaViC was developed specifically to identify novel virus sequence signatures from high throughput sequencing (HTS) datasets in the absence of a known host genome. MetaViC is a protein centric pipeline that looks for specific protein signatures in the reads and contigs generated as part of the pipeline. Several novel viruses, including an alphanodavirus with both segments, a novel relative of the Hubei sobemo-like virus 49, two rhabdo-like viruses and a chuvirus, were identified in the Scottish midge samples. The newly identified viruses were found to be phylogenetically distinct to those previous known. These findings expand our current knowledge of viral diversity in arthropods and especially in these understudied disease vectors.

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“…The additional assumption of mPTP, that the genetic variation may differ substantially among species allows to accurately delimit species in large (meta-) barcoding datasets comprising multiple species of diverse life histories (Kapli et al, 2017). Experiments using empirical data for several animal phyla (Kapli et al, 2017) and recently also viruses (Thézé et al, 2018;Modha et al, 2018) show that the method consistently provides extremely fast and sensible species estimates on 'classic' phylogenetic marker and barcoding genes.…”

Section: Taxonomy Of Viruses) Has Mainly Been Based On Established Bimentioning

confidence: 99%

Peer Review #1 of "Automated, phylogeny-based genotype delimitation of the Hepatitis Viruses HBV and HCV (v0.1)"

Cerrudo¹

2019

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The classification of hepatitis viruses still predominantly relies on ad hoc criteria, i.e., phenotypic traits and arbitrary genetic distance thresholds. Given the subjectivity of such practices coupled with the constant sequencing of samples and discovery of new strains, this manual approach to virus classification becomes cumbersome and impossible to generalize. Methods: Using two well-studied hepatitis virus datasets, HBV and HCV, we assess if computational methods for molecular species delimitation that are typically applied to barcoding biodiversity studies can also be successfully deployed for hepatitis virus classification. For comparison, we also used ABGD, a tool that in contrast to other distance methods attempts to automatically identify the barcoding gap using pairwise genetic distances for a set of aligned input sequences. Results-Discussion: We find that, the mPTP species delimitation tool identified even without adapting its default parameters taxonomic clusters that either correspond to the currently acknowledged genotypes or to known subdivision of genotypes (subtypes or subgenotypes). In the cases where the delimited cluster corresponded to subtype or subgenotype, there were previous concerns that their status may be underestimated. The clusters obtained from the ABGD analysis differed depending on the parameters used. However, under certain values the results were very similar to the taxonomy and mPTP which indicates the usefulness of distance based methods in virus taxonomy under appropriate parameter settings. The overlap of predicted clusters with taxonomically acknowledged genotypes implies that virus classification can be successfully automated.

show abstract

ViCTree: an automated framework for taxonomic classification from protein sequences

Cited by 8 publications

References 28 publications

Automated, phylogeny-based genotype delimitation of the Hepatitis Viruses HBV and HCV

Automated, phylogeny-based genotype delimitation of the Hepatitis Viruses HBV and HCV

Metaviromics Reveals Unknown Viral Diversity in the Biting Midge Culicoides impunctatus

Peer Review #1 of "Automated, phylogeny-based genotype delimitation of the Hepatitis Viruses HBV and HCV (v0.1)"

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