DRAM-v, or DRAM for vMAGs, will annotate vMAGs and predict potential auxiliary metabolic genes, through a set of rules defined in https://academic.oup.com/nar/article/48/16/8883/5884738.

DRAM for vMAGs works by annotating viral genomes with a set of databases curated to the task, and integrating additional input from Virsorter. Note that you must start with a metagenomic assembly object and run the VirSorter KBase app. DRAM-v is run using the viral genome files along with the lshock ID from the KBase VirSorter Summary. The user is then given a tab delimited annotations file with all annotations from all databases for all genes in all genomes, with data on known and potential Auxiliary Metabolic Genes (AMGs). Additionally, the user is given a folder with genbank files for each viral genome, a gff file with all annotations across all genomes, as well as annotated nucleotide and amino acid fasta files of all genes. The results of annotation are distilled. This generates three files: 1. The VMAG statistics which includes all statistics required by MIMAG, 2. The AMG summary which includes relevant statistics on potential AMG genes and 3. The product, which is an interactive heatmap showing potential AMGs for all vMAGs, the number of potential AMGs in each contig, and a heatmap of all possible Distillate categories to which each AMG (category 1 3, default) belongs.