A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data

Author:

Chen Shifu1,He Changshou2,Li Yingqiang2,Li Zhicheng3,Melançon Charles E4

Affiliation:

1. Shenzhen 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

2. department of bioinformatics, HaploX Biotechnology

3. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. His research interests lie mainly in imaging genomics

4. department of research and development, HaploX Biotechnology. His research interests lie mainly in next-generation sequencing and bioinformatics

Abstract

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.

Funder

Development and Reform Commission of Shenzhen Municipality

Shenzhen Science and Technology Innovation Commission

Ministry of Industry and Information Technology

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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