A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing.

Next Generation Sequencing technologies have significant impacts on 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 the raw data, in part 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 the establishment of 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 solutions and future steps, related to different aspects of the design of the 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.

PETRILLO Mauro;  FABBRI Marco;  KAGKLI Dafni Maria;  QUERCI Maddalena;  VAN DEN EEDE Guy;  ALM Erik;  AYTAN Derya;  CAPELLA-GUTTIEREZ Salvador;  CARRILLO Catherine;  CESTARO Alessandro;  CHAN Kok-Gan;  COQUE Teresa Maria;  ENDRULLAT Christoph;  GUT Ivo;  HAMMER Paul;  KAY Gemma;  MADEC Jean-Yves;  MATHER Alison;  MCHARDY Alice;  NAAS Thierry;  PARACCHINI Valentina;  SILKE Peter;  PIGHTLING Arthur;  RAFFAEL Barbara;  ROSSEN John;  RUPPE Etienne;  SCHLABERG Robert;  VANNESTE Kevin;  WEBER Lukas;  WESTH Henrik;  ANGERS Alexandre; 

2022-12-13

F1000 RESEARCH LTD.

JRC122477

2046-1402 (online),   

https://doi.org/10.12688/f1000research.39214.2,    https://publications.jrc.ec.europa.eu/repository/handle/JRC122477,   

10.12688/f1000research.39214.2 (online),