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Updated: Dec 7, 2025

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example
Published on: March 11, 2020
A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data
Shifu Chen1, Changshou He2, Yingqiang Li2
1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. He also serves as chief technology officer of HaploX Biotechnology. He is the initiator of OpenGene projects and a contributor to many open source tools.
Abstract:
In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.
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