Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes
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Abstract
Summary
Genome detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next-generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present the Genome Detective Coronavirus Typing Tool that can accurately identify the novel severe acute respiratory syndrome (SARS)-related coronavirus (SARS-CoV-2) sequences isolated in China and around the world. The tool can accept up to 2000 sequences per submission and the analysis of a new whole-genome sequence will take approximately 1 min. The tool has been tested and validated with hundreds of whole genomes from 10 coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for SARS-CoV-2. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines to stop the COVID-19 disease.
Availability and implementation
https://www.genomedetective.com/app/typingtool/cov
Contact
koen@emweb.be or deoliveira@ukzn.ac.za
Supplementary information
Supplementary data are available at Bioinformatics online.
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SciScore for 10.1101/2020.01.31.928796: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources A reference dataset of previously published coronavirus whole genome sequences (WGS) was compiled from the Virus Pathogen Resource (VIPR) database (www.viprbrc.org). WGSsuggested: NoneVIPRsuggested: (vipR, RRID:SCR_010685)The 431 reference WGS were aligned with MUSCLE (Edgar 2004). MUSCLEsuggested: (MUSCLE, RRID:SCR_011812)A Maximum likelihood phylogenetic tree, 1000 bootstrap replicates was constructed in PhyML (Guidon & Gascuel 2003; Lemoine et al., 2018) and a Bayesian tree using MrBayes (Ronquist & Huelsenbeck 2003) were constructed. PhyMLsuggested: (PhyML, RRID:SCR_014629)MrBayessuggeste…SciScore for 10.1101/2020.01.31.928796: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources A reference dataset of previously published coronavirus whole genome sequences (WGS) was compiled from the Virus Pathogen Resource (VIPR) database (www.viprbrc.org). WGSsuggested: NoneVIPRsuggested: (vipR, RRID:SCR_010685)The 431 reference WGS were aligned with MUSCLE (Edgar 2004). MUSCLEsuggested: (MUSCLE, RRID:SCR_011812)A Maximum likelihood phylogenetic tree, 1000 bootstrap replicates was constructed in PhyML (Guidon & Gascuel 2003; Lemoine et al., 2018) and a Bayesian tree using MrBayes (Ronquist & Huelsenbeck 2003) were constructed. PhyMLsuggested: (PhyML, RRID:SCR_014629)MrBayessuggested: (MrBayes, RRID:SCR_012067)The first classification analysis subjects a query sequence to BLAST and AGA analysi. BLASTsuggested: (BLASTX, RRID:SCR_001653)AGA is a novel alignment method for nucleic acid sequences against annotated genomes from NCBI RefSeq Virus Database. AGA (Deforche 2017) expands the optimal alignment algorithms of Smith-Waterman (Smith & Waterman 1981) and Gotoh (Gotoh 1982) based on an induction state with additional parameters. RefSeqsuggested: (RefSeq, RRID:SCR_003496)In the second step, a query sequence is aligned against the phylogenetic reference dataset using -add alignment option in the MAFFT software (Katoh & Standley 2013). MAFFTsuggested: (MAFFT, RRID:SCR_011811)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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