Critical Assessment of Metagenome Interpretation - A benchmark of metagenomics software
Alexander Sczyrba,Peter Hofmann,Peter Hofmann,Peter Belmann,David Koslicki,Stefan Janssen,Johannes Dröge,Johannes Dröge,Ivan Gregor,Ivan Gregor,Stephan Majda,Jessika Fiedler,Eik Dahms,Eik Dahms,Andreas Bremges,Adrian Fritz,Ruben Garrido-Oter,Tue Sparholt Jørgensen,Tue Sparholt Jørgensen,Tue Sparholt Jørgensen,Nicole Shapiro,Philip D. Blood,Alexey Gurevich,Yang Bai,Dmitrij Turaev,Matthew Z. DeMaere,Rayan Chikhi,Niranjan Nagarajan,Christopher Quince,Fernando Meyer,Monika Balvočiūtė,Lars Hestbjerg Hansen,Søren J. Sørensen,Burton Kuan Hui Chia,Bertrand Denis,Jeff Froula,Zhong Wang,Robert Egan,Dongwan Don Kang,Jeffrey J. Cook,Charles Deltel,Michael Beckstette,Claire Lemaitre,Pierre Peterlongo,Guillaume Rizk,Dominique Lavenier,Yu Wei Wu,Yu Wei Wu,Steven W. Singer,Steven W. Singer,Chirag Jain,Marc Strous,Heiner Klingenberg,Peter Meinicke,Michael D. Barton,Thomas Lingner,Hsin-Hung Lin,Yu-Chieh Liao,Genivaldo G. Z. Silva,Daniel A. Cuevas,Robert Edwards,Surya Saha,Vitor C. Piro,Vitor C. Piro,Bernhard Y. Renard,Mihai Pop,Hans-Peter Klenk,Markus Göker,Nikos C. Kyrpides,Tanja Woyke,Julia A. Vorholt,Paul Schulze-Lefert,Edward M. Rubin,Aaron E. Darling,Thomas Rattei,Alice C. McHardy +75 more
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TLDR
The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups as discussed by the authors.Abstract:
Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were 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 family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.read more
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Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin
Nicholas A. Bokulich,Benjamin D. Kaehler,Jai Ram Rideout,Matthew R. Dillon,Evan Bolyen,Rob Knight,Gavin A. Huttley,J. Gregory Caporaso +7 more
TL;DR: The results illustrate the importance of parameter tuning for optimizing classifier performance, and the recommendations regarding parameter choices for these classifiers under a range of standard operating conditions are made.
Journal ArticleDOI
MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies.
Dongwan D. Kang,Feng Li,Edward Kirton,Ashleigh Thomas,Rob Egan,Hong An,Zhong Wang,Zhong Wang,Zhong Wang +8 more
TL;DR: Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed, and recommends the community adopts Meta BAT 2 for their meetagenome binning experiments.
Journal ArticleDOI
Species-level functional profiling of metagenomes and metatranscriptomes.
Eric A. Franzosa,Eric A. Franzosa,Lauren J. McIver,Lauren J. McIver,Gholamali Rahnavard,Gholamali Rahnavard,Luke R. Thompson,Melanie Schirmer,Melanie Schirmer,George Weingart,Karen Schwarzberg Lipson,Rob Knight,J. Gregory Caporaso,Nicola Segata,Curtis Huttenhower,Curtis Huttenhower +15 more
TL;DR: HUMAnN2 is developed, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities and introduces ‘contributional diversity’ to explain patterns of ecological assembly across different microbial community types.
Journal ArticleDOI
Best practices for analysing microbiomes.
Rob Knight,Alison Vrbanac,Bryn C. Taylor,Alexander A. Aksenov,Chris Callewaert,Chris Callewaert,Justine W. Debelius,Antonio Gonzalez,Tomasz Kosciolek,Laura-Isobel McCall,Daniel McDonald,Alexey V. Melnik,James T. Morton,Jose Navas,Robert A. Quinn,Jon G. Sanders,Austin D. Swafford,Luke R. Thompson,Luke R. Thompson,Anupriya Tripathi,Zhenjiang Zech Xu,Jesse R. Zaneveld,Qiyun Zhu,J. Gregory Caporaso,Pieter C. Dorrestein,Pieter C. Dorrestein +25 more
TL;DR: This Review focuses on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis.
Journal ArticleDOI
MetaWRAP-a flexible pipeline for genome-resolved metagenomic data analysis.
TL;DR: MetaWRAP is an easy-to-use modular pipeline that automates the core tasks in metagenomic analysis, while contributing significant improvements to the extraction and interpretation of high-quality metagenomics bins.
References
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TL;DR: The Human Microbiome Project Consortium reported the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome as discussed by the authors.
Journal ArticleDOI
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Catherine A. Lozupone,Rob Knight +1 more
TL;DR: The results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.
Journal ArticleDOI
SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB
Elmar Pruesse,Christian Quast,Katrin Knittel,Bernhard M. Fuchs,Wolfgang Ludwig,Jörg Peplies,Frank Oliver Glöckner +6 more
TL;DR: SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains.
Journal ArticleDOI
Enterotypes of the human gut microbiome
Manimozhiyan Arumugam,Jeroen Raes,Eric Pelletier,Denis Le Paslier,Takuji Yamada,Daniel R. Mende,Gabriel Fernandes,Julien Tap,Thomas Brüls,Jean-Michel Batto,Marcelo Bertalan,Natalia Borruel,Francesc Casellas,Leyden Fernández,Laurent Gautier,Torben Hansen,Masahira Hattori,Tetsuya Hayashi,Michiel Kleerebezem,Ken Kurokawa,Marion Leclerc,Florence Levenez,Chaysavanh Manichanh,H. Bjørn Nielsen,Trine Nielsen,Nicolas Pons,Julie Poulain,Junjie Qin,Thomas Sicheritz-Pontén,Sebastian Tims,David Torrents,Edgardo Ugarte,Erwin G. Zoetendal,Jun Wang,Francisco Guarner,Oluf Pedersen,Willem M. de Vos,Søren Brunak,Joël Doré,Jean Weissenbach,S. Dusko Ehrlich,Peer Bork +41 more
TL;DR: Three robust clusters (referred to as enterotypes hereafter) are identified that are not nation or continent specific and confirmed in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous.
Journal ArticleDOI
MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph
TL;DR: MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner and generated a three-time larger assembly, with longer contig N50 and average contig length.