CoVEx: SARS-CoV-2 Mutation Explorer for genomic surveillance

Abstract

Effective management of emerging diseases relies on timely pathogen identification and monitoring. The emergence of COVID-19 in December 2019, rapidly evolved into a global pandemic, with millions of cases and deaths reported worldwide. The accumulation of SARS-CoV-2 genomes provided unprecedented opportunities for studying the virus's evolutionary dynamics, understanding the impact of mutations, and identifying emerging Variants of Interest (VOIs) and Variants of Concern (VOCs). During the COVID-19 pandemic, health systems faced challenges in promptly detecting such variants and timely notifying. To facilitate the continuous monitoring of mutations, various initiatives and open-source pipelines have been established. However, these platforms often lack integration for conducting user sequence analysis and comparing it with publicly reported data on platforms like GISAID. Here, we present CoVEx, an easy-to-use tool for analyzing and visualizing SARS-CoV-2 variant sequences obtained using Illumina sequencing technology. CoVEx integrates quality control, alignment, genome annotation, lineage designation, and mutation analysis tools. Implemented in Python, CoVEx also has a mutation explorer feature that generates interactive graphs summarising identified mutations in an intuitive manner. Similarly, it leverages the Outbreak.info package to create heatmaps highlighting the mutations associated with designated Pangolin lineages. Furthermore, by comparing mutation profiles against GISAID data, CoVEx offers valuable insights into the prevalence and distribution of mutations worldwide. We validated CoVEx using raw sequence data (n = 108) and demonstrated its accuracy in assembling sequences and predicting Pangolin and Nextclade Pango lineages. Notably, the tool revealed the emergence of a previously unreported mutation, ORF1a:I2501T, within the Costa Rica GN.1 lineage. This finding highlights CoVEx's capability to identify novel mutations in the different lineages, providing valuable information to researchers and public health decision makers. CoVEx and documentation are freely available on GitLab: https://gitlab.com/CNCA_CeNAT/covex.