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

Serdari, D.; Kostaki, E.-G.; Paraskevis, D.; Stamatakis, A. 1; Kapli, P.
1 Institut für Theoretische Informatik (ITI), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Background
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 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. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000099788
Veröffentlicht am 13.11.2019
Originalveröffentlichung
DOI: 10.7717/peerj.7754
Scopus
Zitationen: 2
Web of Science
Zitationen: 2
Dimensions
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 2167-8359
KITopen-ID: 1000099788
Erschienen in PeerJ
Verlag PeerJ
Band 2019
Heft 10
Seiten Article No.e7754
Vorab online veröffentlicht am 25.10.2019
Nachgewiesen in Dimensions
Scopus
Web of Science
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