A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing [version 2; peer review: 1 approved, 2 approved with reservations]

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon t...

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Main Authors: Alison E. Mather, Alice Carolyn McHardy, Ivo Gut, Gemma L. Kay, Kevin Vanneste, Arthur Pightling, John Rossen, Thierry Naas, Silke Peter, Henrik Westh, Alexandre Angers-Loustau, Etienne Ruppé, Robert Schlaberg, Marco Fabbri, Alessandro Cestaro, Maddalena Querci, Barbara Raffael, Mauro Petrillo, Paul Hammer, Lukas M. Weber, Jean-Yves Madec, Valentina Paracchini, Guy Van den Eede, Erik Alm, Derya Aytan-Aktug, Dafni Maria Kagkli, Teresa Coque, Kok-Gan Chan, Christoph Endrullat, Salvador Capella-Gutierrez, Catherine Carrillo
Format: Article
Language:English
Published: F1000 Research Ltd 2022-03-01
Series:F1000Research
Subjects:
Online Access:https://f1000research.com/articles/10-80/v2
Description
Summary:Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
ISSN:2046-1402