Staff View: A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

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

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...

Full description

Saved in:

Bibliographic Details
Main Authors:	Petrillo, Mauro, Fabbri, Marco, Kagkli, Dafni Maria, Querci, Maddalena, Van den Eede, Guy, Alm, Erik, Aytan-Aktug, Derya, Capella-Gutierrez, Salvador, Carrillo, Catherine, Cestaro, Alessandro, Chan, Kok-Gan, Coque, Teresa, Endrullat, Christoph, Gut, Ivo, Hammer, Paul, Kay, Gemma L., Madec, Jean-Yves, Mather, Alison E., McHardy, Alice Carolyn, Naas, Thierry, Paracchini, Valentina, Peter, Silke, Pightling, Arthur, Raffael, Barbara, Rossen, John, Ruppé, Etienne, Schlaberg, Robert, Vanneste, Kevin, Weber, Lukas M., Westh, Henrik, Angers-Loustau, Alexandre
Format:	Article
Published:	F1000 Research Ltd 2022
Subjects:	Q Science (General)
Online Access:	http://eprints.um.edu.my/43564/
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.um.eprints.43564
record_format	eprints
spelling	my.um.eprints.435642023-10-25T08:24:49Z http://eprints.um.edu.my/43564/ A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing Petrillo, Mauro Fabbri, Marco Kagkli, Dafni Maria Querci, Maddalena Van den Eede, Guy Alm, Erik Aytan-Aktug, Derya Capella-Gutierrez, Salvador Carrillo, Catherine Cestaro, Alessandro Chan, Kok-Gan Coque, Teresa Endrullat, Christoph Gut, Ivo Hammer, Paul Kay, Gemma L. Madec, Jean-Yves Mather, Alison E. McHardy, Alice Carolyn Naas, Thierry Paracchini, Valentina Peter, Silke Pightling, Arthur Raffael, Barbara Rossen, John Ruppé, Etienne Schlaberg, Robert Vanneste, Kevin Weber, Lukas M. Westh, Henrik Angers-Loustau, Alexandre Q Science (General) 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. © 2022 Petrillo M et al. F1000 Research Ltd 2022 Article PeerReviewed Petrillo, Mauro and Fabbri, Marco and Kagkli, Dafni Maria and Querci, Maddalena and Van den Eede, Guy and Alm, Erik and Aytan-Aktug, Derya and Capella-Gutierrez, Salvador and Carrillo, Catherine and Cestaro, Alessandro and Chan, Kok-Gan and Coque, Teresa and Endrullat, Christoph and Gut, Ivo and Hammer, Paul and Kay, Gemma L. and Madec, Jean-Yves and Mather, Alison E. and McHardy, Alice Carolyn and Naas, Thierry and Paracchini, Valentina and Peter, Silke and Pightling, Arthur and Raffael, Barbara and Rossen, John and Ruppé, Etienne and Schlaberg, Robert and Vanneste, Kevin and Weber, Lukas M. and Westh, Henrik and Angers-Loustau, Alexandre (2022) A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing. F1000Research, 10 (80). ISSN 2046-1402, DOI https://doi.org/10.12688/f1000research.39214.2 <https://doi.org/10.12688/f1000research.39214.2>. 10.12688/f1000research.39214.2
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	Q Science (General)
spellingShingle	Q Science (General) Petrillo, Mauro Fabbri, Marco Kagkli, Dafni Maria Querci, Maddalena Van den Eede, Guy Alm, Erik Aytan-Aktug, Derya Capella-Gutierrez, Salvador Carrillo, Catherine Cestaro, Alessandro Chan, Kok-Gan Coque, Teresa Endrullat, Christoph Gut, Ivo Hammer, Paul Kay, Gemma L. Madec, Jean-Yves Mather, Alison E. McHardy, Alice Carolyn Naas, Thierry Paracchini, Valentina Peter, Silke Pightling, Arthur Raffael, Barbara Rossen, John Ruppé, Etienne Schlaberg, Robert Vanneste, Kevin Weber, Lukas M. Westh, Henrik Angers-Loustau, Alexandre A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
description	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. © 2022 Petrillo M et al.
format	Article
author	Petrillo, Mauro Fabbri, Marco Kagkli, Dafni Maria Querci, Maddalena Van den Eede, Guy Alm, Erik Aytan-Aktug, Derya Capella-Gutierrez, Salvador Carrillo, Catherine Cestaro, Alessandro Chan, Kok-Gan Coque, Teresa Endrullat, Christoph Gut, Ivo Hammer, Paul Kay, Gemma L. Madec, Jean-Yves Mather, Alison E. McHardy, Alice Carolyn Naas, Thierry Paracchini, Valentina Peter, Silke Pightling, Arthur Raffael, Barbara Rossen, John Ruppé, Etienne Schlaberg, Robert Vanneste, Kevin Weber, Lukas M. Westh, Henrik Angers-Loustau, Alexandre
author_facet	Petrillo, Mauro Fabbri, Marco Kagkli, Dafni Maria Querci, Maddalena Van den Eede, Guy Alm, Erik Aytan-Aktug, Derya Capella-Gutierrez, Salvador Carrillo, Catherine Cestaro, Alessandro Chan, Kok-Gan Coque, Teresa Endrullat, Christoph Gut, Ivo Hammer, Paul Kay, Gemma L. Madec, Jean-Yves Mather, Alison E. McHardy, Alice Carolyn Naas, Thierry Paracchini, Valentina Peter, Silke Pightling, Arthur Raffael, Barbara Rossen, John Ruppé, Etienne Schlaberg, Robert Vanneste, Kevin Weber, Lukas M. Westh, Henrik Angers-Loustau, Alexandre
author_sort	Petrillo, Mauro
title	A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
title_short	A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
title_full	A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
title_fullStr	A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
title_full_unstemmed	A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
title_sort	roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing
publisher	F1000 Research Ltd
publishDate	2022
url	http://eprints.um.edu.my/43564/
_version_	1781704679821934592
score	13.211869

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

Similar Items