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BACKGROUND: COVID-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 OBJECTIVE: To address these challenges, we developed CoV-Seq, an integrated webserver to enable simple and rapid analysis of SARS-CoV-2 genomes METHODS: Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis A command-line interface is also available for high-throughput processing Also, we aggregate all publicly available SARS-CoV-2 sequences from GISAID, NCBI, ENA, and CNGB, and extract genetic variants from these sequences for download and downstream analysis The CoV-Seq database is updated weekly RESULTS: CoV-Seq is implemented in Python and JavaScript The web server is available at http://covseq baidu com/ and the source code is available from https://github com/boxiangliu/covseq CONCLUSIONS: We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences The web server provides an interactive module for the analysis of custom sequences and weekly updated database of genetic variants from all publicly accessible SARS-CoV-2 sequences We hope CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19
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