VIBRANT (Virus Identification By iteRative ANoTation) is an automated software tool for the recovery and annotation of bacterial/archaeal viruses, determination of genome quality and completeness, and metabolic gene identification. Highlighting viral auxiliary metabolic genes (AMGs) and metabolic pathways further allows the software to serve as a platform for evaluating viral community function. VIBRANT’s method utilizes a hybrid neural network machine learning and protein similarity approach (KEGG, Pfam and VOG protein databases) to maximize identification of lytic viral genomes and integrated proviruses, including highly diverse viruses. It achieves high accuracy and recovery due to the use of a newly described “v-score” metric to quantify virus-association of each protein annotation. VIBRANT was designed for use with complex metagenomic samples but also functions to identify viruses from cultivated or simple systems.
VIBRANT was designed to be fast, accurate and user-friendly. At minimum the only input required is a single file containing unknown sequences (genomes, MAGs, scaffolds). The outputs include a variety of useful sets of information in addition to the identified viruses in FASTA and GenBank formats. These additional outputs include the following: simple visualizations of AMG pathways and viral metrics (number, quality and sizes), spreadsheet files for AMG details (names, counts and pathways), protein annotation information (full annotations per database and best hit annotation per protein), identified circular viruses, and a summary spreadsheet of all identification metric information per virus.
Check out VIBRANT on GitHub
Read our manuscript at Microbiome