vsRNAfinder: a novel method for identifying high-confidence viral small RNAs from small RNA-Seq data

Virus-encoded small RNAs (vsRNA) have been reported to play an important role in viral infection. Unfortunately, there is still a lack of an effective method for vsRNA identification. Herein, we presented vsRNAfinder, a de novo method for identifying high-confidence vsRNAs from small RNA-Seq (sRNA-Seq) data based on peak calling and Poisson distribution and is publicly available at https://github. com/ZenaCai/vsRNAfinder. vsRNAfinder outperformed two widely used methods namely miRDeep2 and ShortStack in identifying viral miRNAs with a significantly improved sensitivity. It can also be used to identify sRNAs in animals and plants with similar performance to miRDeep2 and ShortStack. vsRNAfinder would greatly facilitate effective identification of vsRNAs from sRNA-Seq data.

Automated summary

vsRNAfinder is a de novo method for identifying high-confidence vsRNAs from sRNA-Seq data, which outperforms widely used methods in identifying viral miRNAs and shows similar performance in animal and plant sRNAs identification. It greatly facilitates the effective identification of vsRNAs from sRNA-Seq data.