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Cited by 870

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software

Open access
Sczyrba, Alexander, Hofmann, Peter, Belmann, Peter, Koslicki, David, Janssen, Stefan, Dröge, Johannes, Gregor, Ivan, Majda, Stephan, Fiedler, Jessika, Dahms, Eik, Bremges, Andreas, Fritz, Adrian, Garrido-Oter, Ruben, Jørgensen, Tue Sparholt, Shapiro, Nicole, Blood, Philip D, Gurevich, Alexey, Bai, Yang, Turaev, Dmitrij, DeMaere, Matthew Z, Chikhi, Rayan, Nagarajan, Niranjan, Quince, Christopher, Meyer, Fernando, Balvočiūtė, Monika, Hansen, Lars Hestbjerg, Sørensen, Søren J, Chia, Burton K H, Denis, Bertrand, Froula, Jeff L, Wang, Zhong, Egan, Robert, Don Kang, Dongwan, Cook, Jeffrey J, Deltel, Charles, Beckstette, Michael, Lemaitre, Claire, Peterlongo, Pierre, Rizk, Guillaume, Lavenier, Dominique, Wu, Yu-Wei, Singer, Steven W, Jain, Chirag, Strous, Marc, Klingenberg, Heiner, Meinicke, Peter, Barton, Michael D, Lingner, Thomas, Lin, Hsin-Hung, Liao, Yu-Chieh, Silva, Genivaldo Gueiros Z, Cuevas, Daniel A, Edwards, Robert A, Saha, Surya, Piro, Vitor C, Renard, Bernhard Y, Pop, Mihai, Klenk, Hans-Peter, Göker, Markus, Kyrpides, Nikos C, Woyke, Tanja, Vorholt, Julia A, Schulze-Lefert, Paul, Rubin, Edward M, Darling, Aaron E, Rattei, Thomas, McHardy, Alice C·2017·Nature Methods
DOI 10.1038/nmeth.4458
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Abstract

Abstract In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

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Authors
Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., Majda, S., Fiedler, J., Dahms, E., Bremges, A., Fritz, A., Garrido-Oter, R., Jørgensen, T. S., Shapiro, N., Blood, P. D., Gurevich, A., Bai, Y., Turaev, D., DeMaere, M. Z., Chikhi, R., Nagarajan, N., Quince, C., Meyer, F., Balvočiūtė, M., Hansen, L. H., Sørensen, S. J., Chia, B. K. H., Denis, B., Froula, J. L., Wang, Z., Egan, R., Don Kang, D., Cook, J. J., Deltel, C., Beckstette, M., Lemaitre, C., Peterlongo, P., Rizk, G., Lavenier, D., Wu, Y.-W., Singer, S. W., Jain, C., Strous, M., Klingenberg, H., Meinicke, P., Barton, M. D., Lingner, T., Lin, H.-H., Liao, Y.-C., Silva, G. G. Z., Cuevas, D. A., Edwards, R. A., Saha, S., Piro, V. C., Renard, B. Y., Pop, M., Klenk, H.-P., Göker, M., Kyrpides, N. C., Woyke, T., Vorholt, J. A., Schulze-Lefert, P., Rubin, E. M., Darling, A. E., Rattei, T., & McHardy, A. C.
Venue
Nature Methods
Publisher
Springer Science and Business Media LLC
Published
2017-10-02
Volume
14
Issue
11
Pages
1063-1071
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
DOI
10.1038/nmeth.4458
OpenAlex
W2773939681
Cited by
870
References
8
FWCI
33.58
Type
journal article
Language
en
Open access
hybrid

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