Abstract
Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called “megataxonomy of viruses”, recognizes five different viral realms, defined based on the presence of viral hallmark genes. Within the realms, viruses are classified into hierarchical taxons, ideally defined by their shared genes. Therefore, there is currently a need for virus classification tools based on such shared genes / proteins. Here, VirClust is presented – a novel tool capable of performing i) hierarchical clustering of viruses based on intergenomic distances calculated from their protein cluster content, ii) identification of core proteins and iii) annotation of viral proteins. VirClust groups proteins into clusters both based on BLASTP sequence similarity, which identifies more related proteins, and also based on hidden markow models (HMM), which identifies more distantly related proteins. Furthermore, VirClust provides an integrated visualization of the hierarchical clustering tree and of the distribution of the protein content, which allows the identification of the genomic features responsible for the respective clustering. By using different intergenomic distances, the hierarchical trees produced by VirClust can be split into viral genome clusters of different taxonomic ranks. VirClust is freely available, as web-service (virclust.icbm.de) and stand-alone tool.
Competing Interest Statement
The authors have declared no competing interest.
