Identification of bioinformatic pipelines for virus monitoring using nanopore sequence data: A systematic assessment - Kaiser, Nick Laurenz; Groschup, Martin H.; Sadeghi, Balal (Journal of virological methods, 2025)
Nanopore sequencing has proven to be a promising technique in virus surveillance efforts, especially due to the portability of its sequencers. In order to process the long, error-prone reads generated, specialised bioinformatic programs are required. These can be run automatically within pipelines so as to effectively provide decision makers with all relevant information about the molecular characteristics of a virus. The purpose of this systematic assessment was to identify pipelines that are suitable for virus surveillance programs using nanopore sequencing. Promising candidates were then compared in terms of their functional scope. Of 239 initial papers, 22 pipelines were tested, of which six were included in the final assessment. The four pipelines that were exclusively available offline were each missing individual downstream analysis steps considered in our assessment. The other two executed all steps. One of these was only available online and subject to a charge, while the other was freely available both online and offline. While we were able to identify two pipelines that are broadly suitable for virus surveillance using nanopore sequencing, we discovered two major shortcomings in this domain. None of the pipelines integrated basecalling, the initial step of data processing. In addition, there was no pipeline that was easy to install and provided all relevant analysis results with a single program call. We therefore see a need for the development of a pipeline that incorporates both aspects. •Evaluates bioinformatic pipelines for virus monitoring using nanopore sequencing, highlighting strengths and weaknesses.•Identifies usability challenges, such as lack of easy installation, offline execution, and basecalling integration.•Focuses on improving viral detection accuracy, especially for variants and quasi-species, to enhance diagnostics and early outbreak detection.