In the output directory (test.out), three files are useful: Virsorter run -w test.out -i test.fa -min-length 1500 -j 4 allĭue to the large HMM database that VirSorter2 uses, this small dataset takes a few mins to finish. # run classification with 4 threads (-j) and test-out as output diretory (-w) If you do not have conda installed, it can be installed following this link. Installation (tested on CentOS linux should work in all linux MacOS is not supported at the moment) Option 1 (bioconda version)Ĭonda is the easiest way to install VirSorter2.
A new FAQ section is available at the bottom of this doc.
The default -include-groups is changed from all viral groups to dsDNAphage and ssDNA since this should be used for most people interested in phage.
A few new options are added to accommodate the SOP (see details in change log).
2.2.3 TESTOUT LAB HOW TO
A tutorial/SOP on how to quality control VirSorter2 results is avaiable here.
train with high quality virus genomes from metagenomes or other sources.
apply machine learning to estimate viralness using genomic features including structural/functional/taxonomic annotation and viral hallmark genes.
work with more viral groups including dsDNA phages, ssDNA viruses, RNA viruses, NCLDV (Nucleocytoviricota), lavidaviridae (virophages).
It has made major updates to its previous version: VirSorter2 applies a multi-classifier, expert-guided approach to detect diverse DNA and RNA virus genomes.