Critical Assessment of Metagenome Interpretation: the second round of challenges

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  • Fernando Meyer
  • Adrian Fritz
  • Zhi Luo Deng
  • David Koslicki
  • Till Robin Lesker
  • Alexey Gurevich
  • Gary Robertson
  • Mohammed Alser
  • Dmitry Antipov
  • Francesco Beghini
  • Denis Bertrand
  • Jaqueline J. Brito
  • C. Titus Brown
  • Jan Buchmann
  • Aydin Buluç
  • Bo Chen
  • Rayan Chikhi
  • Philip T.L.C. Clausen
  • Alexandru Cristian
  • Piotr Wojciech Dabrowski
  • Aaron E. Darling
  • Rob Egan
  • Eleazar Eskin
  • Evangelos Georganas
  • Eugene Goltsman
  • Melissa A. Gray
  • Steven Hofmeyr
  • Pingqin Huang
  • Luiz Irber
  • Huijue Jia
  • Tue Sparholt Jørgensen
  • Silas D. Kieser
  • Terje Klemetsen
  • Axel Kola
  • Mikhail Kolmogorov
  • Anton Korobeynikov
  • Jason Kwan
  • Nathan LaPierre
  • Claire Lemaitre
  • Chenhao Li
  • Antoine Limasset
  • Fabio Malcher-Miranda
  • Serghei Mangul
  • Vanessa R. Marcelino
  • Camille Marchet
  • Pierre Marijon
  • Dmitry Meleshko
  • Daniel R. Mende
  • Alessio Milanese
  • Niranjan Nagarajan
  • Sergey Nurk
  • Leonid Oliker
  • Lucas Paoli
  • Pierre Peterlongo
  • Vitor C. Piro
  • Jacob S. Porter
  • Evan R. Rees
  • Knut Reinert
  • Bernhard Renard
  • Espen Mikal Robertsen
  • Gail L. Rosen
  • Hans Joachim Ruscheweyh
  • Varuni Sarwal
  • Nicola Segata
  • Enrico Seiler
  • Lizhen Shi
  • Fengzhu Sun
  • Shinichi Sunagawa
  • Ashleigh Thomas
  • Chengxuan Tong
  • Mirko Trajkovski
  • Julien Tremblay
  • Gherman Uritskiy
  • Riccardo Vicedomini
  • Zhengyang Wang
  • Ziye Wang
  • Zhong Wang
  • Andrew Warren
  • Nils Peder Willassen
  • Katherine Yelick
  • Ronghui You
  • Georg Zeller
  • Zhengqiao Zhao
  • Shanfeng Zhu
  • Jie Zhu
  • Ruben Garrido-Oter
  • Petra Gastmeier
  • Stephane Hacquard
  • Susanne Häußler
  • Ariane Khaledi
  • Friederike Maechler
  • Fantin Mesny
  • Simona Radutoiu
  • Paul Schulze-Lefert
  • Nathiana Smit
  • Till Strowig
  • Andreas Bremges
  • Alexander Sczyrba
  • Alice Carolyn McHardy

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Original languageEnglish
JournalNature Methods
Volume19
Issue number4
Pages (from-to)429-440
ISSN1548-7091
DOIs
Publication statusPublished - 2022

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© 2022, The Author(s).

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