VIRify: an integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models

Abstract

The study of viral communities has revealed the enormous diversity and impact these biological entities have on a range of different ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterization of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterization of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities and a large metagenomics study. The results showed that VIRify was able to identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an accuracy of at least 95.5%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them.

KMCP: accurate metagenomic profiling of both prokaryotic and viral populations by pseudo-mapping

“…We also compare KMCP against established viral detection and annotation software PhaGCN ( Shang et al , 2021 ) and VIRify ( Rangel-Pineros et al , 2022 ) ( Supplementary Section S1.4 ). The taxon identification accuracies at the family rank (the lowest common supported rank by the three tools) showed that all tools had a precision of 1, while KMCP had the highest average recall (0.971), followed by PhaGCN (0.600) and VIRify (0.543).…”

Discovering and exploring the hidden diversity of human gut viruses using highly enriched virome samples

“…We presented here a novel strategy that exploits Viral Like Particle (VLP) enriched viromes as the first crucial step in a multiple-step pipeline for the identification and discovery of potentially new viral sequences. Compared to current methods to label as viral contigs of metagenomic origin 19,24,74 , our approach maximizes the chances of identifying phages with no common characteristics in terms of sequence, structure, or derived features with known phages. This is derived from our specific focus on the metagenomic assemblies from carefully evaluated highly enriched viromes, under the assumption that they would yield more sequences of sure viral origin.…”

Rational Design of Profile HMMs for Sensitive and Specific Sequence Detection with Case Studies Applied to Viruses, Bacteriophages, and Casposons

“…Several collections of profile HMMs are publicly available, including the more generic Pfam database [ 24 ], which is oriented towards protein families, and domain-specific resources, such as VFam [ 54 ], pVOGs [ 53 ], efam [ 58 ], PHROGs [ 59 ], and ViPhOGs [ 60 ], more oriented to the virology community. With the exception of ViPhOGs and VIRify [ 61 ], their accompanying taxonomic classification pipeline, the available models are not provided with cutoff scores, requiring the user to arbitrarily draw the line between significant and non-significant results. Not using cutoff scores at all means that unrelated sequences could be detected.…”

“…However, these databases have not been updated in recent years and present some limitations, such as the highly biased representation of the different viral families and the low number of sequences used to build most of the models [ 34 ]. Some recently developed resources include RVDB-prot [ 55 ], a protein version of the Reference Viral DataBase (RVDB) [ 56 ], viralOGs/eggNOG v5.0 [ 57 ], efam [ 58 ], PHROGs [ 59 ], ViPhOGs [ 60 , 61 ], Cenote-Taker 2 hallmark gene HMM database [ 62 ], and IMG/VR [ 39 ], a database of viral genome sequences of cultivated and uncultivated viruses that includes thousands of profile HMMs. Most if not all available viral databases provide profile HMMs derived from MSAs containing orthologs, that is, sequences that are assumed to share a common ancestry and biological function.…”