VirFinder

VirFinder is a bioinformatics tool designed to identify viral sequences within high-throughput metagenomic data. Developed by researchers at the University of Hamburg and the Max Planck Institute for Marine Microbiology, it was first published in 2016 by Ren et al. The software applies a machine‑learning approach based on k‑mer frequency profiles, employing a support vector machine (SVM) classifier to discriminate viral from non‑viral contigs. The training set comprised a large collection of known viral genomes, while the negative set included bacterial, archaeal, eukaryotic, and plasmid sequences. After training, VirFinder scores a sequence from 0 to 1, where values above a user‑defined threshold indicate a high probability of viral origin.

VirFinder accepts contig or read assemblies in FASTA format and is implemented in the R programming language, requiring the e1071 package for SVM functionality. The tool is GPU‑agnostic, making it suitable for deployment on servers or cloud platforms. It can analyze millions of contigs efficiently, producing a table of scores, bit‑scores, and predicted taxonomic relevance.

The method has proven effective for uncovering novel phage genomes in diverse environments, including human microbiome studies, ocean samples, and soil metagenomes. It complements homology‑based approaches such as BLAST, enabling detection of highly divergent viruses lacking homologous references. However, VirFinder’s reliance on k‑mer patterns may limit sensitivity for extremely short reads or for genomes with atypical composition. False positives can arise in host genomes with viral‐like sequences, and the model’s performance depends on the representativeness of its training data.

Overall, VirFinder serves as a rapid, unsupervised screening tool that expands the catalog of viral genetic diversity in metagenomic datasets. Researchers often integrate its outputs with downstream methods such as genome assembly, annotation, and phylogenomic analysis to construct a comprehensive view of viral communities.