To address these challenges, we developed CoV-Seq, an integrated 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 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.

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.

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.