The integration of next-generation sequencing into clinical diagnostics and surveillance initiatives is impeded by the lack of data analysis pipelines that align with privacy legislation and laboratory certification protocols. To address these challenges, we developed Jovian, an open-source, virus-focused, metagenomic analysis workflow for Illumina data. Jovian generates scaffolds enriched with pertinent annotations, including taxonomic classification, combined with metrics needed for quality assessment (coverage depth, average GC content, localization of open reading frames, minority single nucleotide polymorphisms), and incorporates host and disease metadata. Interactive web-based reports with an audit trail are generated. Jovian was employed on four systems, hosted by three institutes, utilizing grid-computers, a high-performance compute singular server, and a Windows10 laptop. All systems yielded identical results with matching MD5sums. Comparison with a commercial online reference tool using viral gastroenteritis samples confirmed the identification of the same pathogens. Jovian provides comparable results to a commercially available online reference tool and generates identical results at different institutes with different IT architectures, proving it is portable and reproducible. Jovian addresses bottlenecks in the deployment of metagenomics within public health and clinical laboratories and has the potential to enhance the breadth of surveillance and testing programs, thereby fostering more effective public health interventions.
Keywords: Clinics; Diagnostics; Next generation sequencing; Public health; Surveillance; Viromics.
© 2024. The Author(s).