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Oxford University Press, Bioinformatics, 4(39), 2023

DOI: 10.1093/bioinformatics/btad160

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

Journal article published in 2023 by Petr Triska, Fabian Amman, Lukas Endler ORCID, Andreas Bergthaler ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Motivation Environmental monitoring of pathogens provides an accurate and timely source of information for public health authorities and policymakers. In the last 2 years, wastewater sequencing proved to be an effective way of detection and quantification of severe acute respiratory syndrome coronavirus 2 (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 these data is crucial for the assessment of the epidemiological situation and forecasting. Here, we present a web-based dashboard application for the 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 (Web-based tool for Analysis and Visualization of Environmental Samples) 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 and implementation WAVES source code is freely available at https://github.com/ptriska/WavesDash under MIT license. A demo version of this application can be accessed at: https://wavesdashboard.azurewebsites.net/.