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Background/Objectives: Clinical surveillance of infectious diseases caused by viruses, such as SARS-CoV-2, is important for effective intervention and preventing potential epidemics or pandemics. The development of cost-effective whole genome sequencing technologies has facilitated worldwide efforts to sequence viral genomes. The array of sequence data generated across the globe offers diverse opportunities to study SARS-CoV-2 evolutionary dynamics and serves as a foundation for different research questions in the future. Even though bioinformatics tools are rapidly developed for accessing and analyzing large-scale data from public repositories, surveillance labs lack streamlined pipelines to handle high sample volumes and efficiently identify mutations for variant reporting with minimal computational expertise. Methods: We have developed a SARS-CoV-2 mutational analysis pipeline using Workflow Description Language (WDL), which is open-source and combines various steps in an analysis workflow with human-readable syntax. Thus, users with minimal informatics background can easily adapt the workflow while creating a local data repository within their institution. The pipeline processes input FASTA files and quality control files from Ion Torrent S5, performs clade and variant assignments, integrates patient metadata, and stores the results into a REDCap database. Results: In this framework, REDCap acts as the core data backbone for run-level tracking and result storage. To further enhance the utility of our REDCap-based data capture system, we have developed an intuitive interactive dashboard. This interface seamlessly connects with the REDCap data sources, providing real-time monitoring, interactive visualization, and the ability to create a consolidated variant report. Conclusions: Our overall approach streamlines processes in managing complex genomic data and offers easy adaptation to empower other molecular labs.
Zimmer et al. (2026) studied this question.