VIGA: an one-stop tool for eukaryotic Virus Identification and Genome Assembly from next-generation-sequencing data

Abstract

Identification of viruses and further assembly of viral genomes from the next-generation-sequencing (NGS) data are essential steps in virome studies. This study presented an one-stop tool named VIGA (available at https://github.com/viralInformatics/VIGA) for eukaryotic virus identification and genome assembly from NGS data. It was composed of four modules including identification, taxonomic annotation, assembly and novel virus discovery which integrated the homology-based method for virus identification and both the reference-based and de novo assemblers for accurate and effective assembly of virus genomes. Evaluation on multiple simulated and real virome datasets showed that VIGA assembled more complete virus genomes than its competitors on both the metatranscriptomic and metagenomic data, and also performed well in assembling virus genomes at the strain level. Finally, VIGA was used to investigate the virome in metatranscriptomic data from the Human Microbiome Project and revealed different composition and positive rate of viromes in diseases of Prediabetes, Crohns disease and Ulcerative colitis. Overall, VIGA would help much in identification and characterization of viromes in future studies.