Standard

Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit. / Meyer, Fernando; Lesker, Till-Robin; Koslicki, David; Fritz, Adrian; Гуревич, Алексей Александрович; Darling, Aaron E.; Sczyrba, Alexander; Bremges, Andreas; McHardy, Alice C.

в: Nature Protocols, Том 16, № 4, 04.2021, стр. 1785-1801.

Результаты исследований: Научные публикации в периодических изданияхОбзорная статьяРецензирование

Harvard

Meyer, F, Lesker, T-R, Koslicki, D, Fritz, A, Гуревич, АА, Darling, AE, Sczyrba, A, Bremges, A & McHardy, AC 2021, 'Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit', Nature Protocols, Том. 16, № 4, стр. 1785-1801. https://doi.org/10.1038/s41596-020-00480-3

APA

Meyer, F., Lesker, T-R., Koslicki, D., Fritz, A., Гуревич, А. А., Darling, A. E., Sczyrba, A., Bremges, A., & McHardy, A. C. (2021). Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit. Nature Protocols, 16(4), 1785-1801. https://doi.org/10.1038/s41596-020-00480-3

Vancouver

Meyer F, Lesker T-R, Koslicki D, Fritz A, Гуревич АА, Darling AE и пр. Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit. Nature Protocols. 2021 Апр.;16(4):1785-1801. https://doi.org/10.1038/s41596-020-00480-3

Author

Meyer, Fernando ; Lesker, Till-Robin ; Koslicki, David ; Fritz, Adrian ; Гуревич, Алексей Александрович ; Darling, Aaron E. ; Sczyrba, Alexander ; Bremges, Andreas ; McHardy, Alice C. / Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit. в: Nature Protocols. 2021 ; Том 16, № 4. стр. 1785-1801.

BibTeX

@article{850bc8a76d7e462fbac506c5ab4a6a96,
title = "Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit",
abstract = "Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.",
author = "Fernando Meyer and Till-Robin Lesker and David Koslicki and Adrian Fritz and Гуревич, {Алексей Александрович} and Darling, {Aaron E.} and Alexander Sczyrba and Andreas Bremges and McHardy, {Alice C.}",
year = "2021",
month = apr,
doi = "10.1038/s41596-020-00480-3",
language = "English",
volume = "16",
pages = "1785--1801",
journal = "Nature Protocols",
issn = "1754-2189",
publisher = "Nature Publishing Group",
number = "4",

}

RIS

TY - JOUR

T1 - Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit

AU - Meyer, Fernando

AU - Lesker, Till-Robin

AU - Koslicki, David

AU - Fritz, Adrian

AU - Гуревич, Алексей Александрович

AU - Darling, Aaron E.

AU - Sczyrba, Alexander

AU - Bremges, Andreas

AU - McHardy, Alice C.

PY - 2021/4

Y1 - 2021/4

N2 - Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.

AB - Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.

UR - http://www.scopus.com/inward/record.url?scp=85101805348&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/af712119-d0ae-3f2a-bcb1-5010080a22bd/

U2 - 10.1038/s41596-020-00480-3

DO - 10.1038/s41596-020-00480-3

M3 - Review article

VL - 16

SP - 1785

EP - 1801

JO - Nature Protocols

JF - Nature Protocols

SN - 1754-2189

IS - 4

ER -

ID: 74772126