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bioRxiv · 10.1101/2020.05.01.071050

CoV-Seq: SARS-CoV-2 Genome Analysis and Visualization

Liu, B.·Liu, K.·Zhang, H.·Zhang, L.·Huang, L.
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Abstract

SummaryCOVID-19 has become a global pandemic not long after its inception in late 2019. SARS-CoV-2 genomes are being sequenced and shared on public repositories at a fast pace. To keep up with these updates, scientists need to frequently refresh and reclean datasets, which is ad hoc and labor-intensive. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. In order to address these challenges, we developed CoV-Seq, a webserver to enable simple and rapid analysis of SARS-CoV-2 genomes. Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are presented in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is also available for high-throughput processing. Availability and ImplementationCoV-Seq is implemented in Python and Javascript. The webserver is available at http://covseq.baidu.com/ and the source code is available from https://github.com/boxiangliu/covseq. Contactjollier.liu@gmail.com Supplementary informationSupplementary information are available at bioRxiv online.

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Liu, B., Liu, K., Zhang, H., Zhang, L., Huang, L.. 2020-05-02. CoV-Seq: SARS-CoV-2 Genome Analysis and Visualization. https://doi.org/10.1101/2020.05.01.071050

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