A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
| Autor: | Marco Fabbri, Valentina Paracchini, Henrik Westh, Mauro Petrillo, Paul Hammer, Barbara Raffael, Guy Van den Eede, Alexandre Angers-Loustau, Derya Aytan-Aktug, Alessandro Cestaro, Alice C. McHardy, Maddalena Querci, Christoph Endrullat, Catherine D. Carrillo, Silke Peter, Jean-Yves Madec, Erik Alm, John W. A. Rossen, Ivo Gut, Dafni-Maria Kagkli, Gemma L. Kay, Alison E. Mather, T. M. Coque, Kevin Vanneste, Thierry Naas, Kok-Gan Chan, Etienne Ruppé, Lukas M. Weber, Salvador Capella-Gutierrez, Robert Schlaberg, Arthur W. Pightling |
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| Přispěvatelé: | Microbes in Health and Disease (MHD) |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
0301 basic medicine
Computer science Bioinformatics media_common.quotation_subject 030106 microbiology Antimicrobial resistance Field (computer science) General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Constant (computer programming) Drug Resistance Bacterial Quality (business) General Pharmacology Toxicology and Pharmaceutics Implementation media_common Flexibility (engineering) General Immunology and Microbiology Computational Biology High-Throughput Nucleotide Sequencing Benchmarking General Medicine Anti-Bacterial Agents 030104 developmental biology Risk analysis (engineering) Next-generation sequencing Raw data |
| Zdroj: | F1000Research, 10:80. F1000Research Petrillo, M, Fabbri, M, Kagkli, D M, Querci, M, Van den Eede, G, Alm, E, Aytan, D, Capella-Gutierrez, S, Carrillo, C, Cestaro, A, Chan, K-G, Coque, T, Endrullat, C, Gut, I, Hammer, P, Kay, G L, Madec, J-Y, Mather, A E, McHardy, A C, Naas, T, Paracchini, V, Peter, S, Pightling, A, Raffael, B, Rossen, J, Ruppé, E, Schlaberg, R, Vanneste, K, Weber, L, Westh, H & Angers-Loustau, A 2021, ' A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing ', F1000Research, vol. 10, 80 . https://doi.org/10.12688/f1000research.39214.1 |
| ISSN: | 2046-1402 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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