WAVES (Web-based tool for Analysis and Visualization of Environmental Samples) – a web application for visualization of wastewater pathogen sequencing results

Environmental monitoring of pathogens provides an accurate and timely source of information for public health authorities and policymakers. In the last two years, wastewater sequencing proved to be an effective way of detection and quantification of SARS-CoV-2 variants circulating in population. Wastewater sequencing produces substantial amounts of geographical and genomic data. Proper visualization of spatial and temporal patterns in this data is crucial for the assessment of the epidemiological situation and forecasting. Here, we present a web-based dashboard application for visualization and analysis of data obtained from sequencing of environmental samples. The dashboard provides multi-layered visualization of geographical and genomic data. It allows to display frequencies of detected pathogen variants as well as individual mutation frequencies. The features of WAVES for early tracking and detection of novel variants in the wastewater are demonstrated in an example of BA.1 variant and the signature Spike mutation S:E484A. WAVES dashboard is easily customized through the editable configuration file and can be used for different types of pathogens and environmental samples. Availability WAVES source code is freely available at under MIT license. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: A waiver of ethical approval was received from the deputy chair of the Ethics commission of the City of Vienna Dr. Tamchina. This current manuscript, a bioinformatic application note how to visualize wastewater-derived viral surveillance data, builds on the manuscript . I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present work are contained in the manuscript and available online in a Github repository.