SUMMARY: Accurate pathogen identification is crucial during outbreaks, especially with the emergence of new variants requiring frequent primer updates. However, resources for maintaining up-to-date verification of primer sequences are often limited, which poses challenges for reliable diagnosis and hinders potential monitoring efforts based on genome sequencing. To address this, we introduce ViralPrimer, a web server facilitating primer design, SARS-CoV-2 and Mpox variant monitoring, and adaptation to future threats. ViralPrimer aims to enhance diagnostic accuracy with its comprehensive primer database, mutation analysis assistance, and user primer upload feature. Its adaptable design allows monitoring of other rapidly mutating pathogens, contributing to broader public health protection efforts. AVAILABILITY AND IMPLEMENTATION: ViralPrimer is freely accessible and open to all users with no login requirement at https://viralprimer.elte.hu/. The application is hosted on a DJANGO v3.2.13 web server, with a PostgreSQL database, and the frontend was implemented using jQuery v3.6.0, vanilla JavaScript vES6, and Bootstrap v5.1.

BACKGROUND: Detection of somatic mutations is one of the main goals of next generation DNA sequencing. A wide range of experimental systems are available for the study of spontaneous or environmentally induced mutagenic processes. However, most of the routinely used mutation calling algorithms are not optimised for the simultaneous analysis of multiple samples, or for non-human experimental model systems with no reliable databases of common genetic variations. Most standard tools either require numerous in-house post filtering steps with scarce documentation or take an unpractically long time to run. To overcome these problems, we designed the streamlined IsoMut tool which can be readily adapted to experimental scenarios where the goal is the identification of experimentally induced mutations in multiple isogenic samples. METHODS: Using 30 isogenic samples, reliable cohorts of validated mutations were created for testing purposes. Optimal values of the filtering parameters of IsoMut were determined in a thorough and strict optimization procedure based on these test sets. RESULTS: We show that IsoMut, when tuned correctly, decreases the false positive rate compared to conventional tools in a 30 sample experimental setup; and detects not only single nucleotide variations, but short insertions and deletions as well. IsoMut can also be run more than a hundred times faster than the most precise state of art tool, due its straightforward and easily understandable filtering algorithm. CONCLUSIONS: IsoMut has already been successfully applied in multiple recent studies to find unique, treatment induced mutations in sets of isogenic samples with very low false positive rates. These types of studies provide an important contribution to determining the mutagenic effect of environmental agents or genetic defects, and IsoMut turned out to be an invaluable tool in the analysis of such data.