ENVirT: inference of ecological characteristics of viruses from metagenomic data
Duleepa Jayasundara, Damayanthi Herath, Damith Senanayake, Isaam Saeed, Cheng-Yu Yang, Yuan Sun, Bill C Chang, Sen-Lin Tang, Saman K Halgamuge
BMC Bioinformatics | BioMed Central | Published : 2019
Background: Estimating the parameters that describe the ecology of viruses,particularly those that are novel, can be made possible using metagenomic approaches. However, the best-performing existing methods require databases to first estimate an average genome length of a viral community before being able to estimate other parameters, such as viral richness. Although this approach has been widely used, it can adversely skew results since the majority of viruses are yet to be catalogued in databases. Results: In this paper, we present ENVirT, a method for estimating the richness of novel viral mixtures, and for the first time we also show that it is possible to simultaneously estimate the av..View full abstract
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Awarded by Australia Research Council
This work was supported partially by Australia Research Council [grant numbers LP140100670 and DP150103512] and the Biodiversity Research Center, Academia Sinica, Taiwan. DJ, DH, DS and YS were funded by the MIFRS and MIRS scholarships of The University of Melbourne. Publication costs were funded by The Australian National University.