Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software

Sczyrba A, Hofmann P, Belmann P, Koslicki D, Janssen S, Dröge J, Gregor I, Majda S, Fiedler J, Dahms E, Bremges A, et al. (2017)
Nature Methods 14(11): 1063-1071.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Sczyrba, AlexanderUniBi ; Hofmann, Peter; Belmann, PeterUniBi; Koslicki, David; Janssen, StefanUniBi ; Dröge, Johannes; Gregor, Ivan; Majda, Stephan; Fiedler, Jessika; Dahms, Eik; Bremges, AndreasUniBi ; Fritz, Adrian
Abstract / Bemerkung
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.
Nature Methods
1548-7091, 1548-7105
Page URI


Sczyrba A, Hofmann P, Belmann P, et al. Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software. Nature Methods. 2017;14(11):1063-1071.
Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., et al. (2017). Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software. Nature Methods, 14(11), 1063-1071.
Sczyrba, Alexander, Hofmann, Peter, Belmann, Peter, Koslicki, David, Janssen, Stefan, Dröge, Johannes, Gregor, Ivan, et al. 2017. “Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software”. Nature Methods 14 (11): 1063-1071.
Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., Majda, S., Fiedler, J., Dahms, E., et al. (2017). Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software. Nature Methods 14, 1063-1071.
Sczyrba, A., et al., 2017. Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software. Nature Methods, 14(11), p 1063-1071.
A. Sczyrba, et al., “Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software”, Nature Methods, vol. 14, 2017, pp. 1063-1071.
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.: Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software. Nature Methods. 14, 1063-1071 (2017).
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, and McHardy, Alice C. “Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software”. Nature Methods 14.11 (2017): 1063-1071.
Link(s) zu Volltext(en)
Access Level
OA Open Access

68 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes.
Chen IA, Chu K, Palaniappan K, Pillay M, Ratner A, Huang J, Huntemann M, Varghese N, White JR, Seshadri R, Smirnova T, Kirton E, Jungbluth SP, Woyke T, Eloe-Fadrosh EA, Ivanova NN, Kyrpides NC., Nucleic Acids Res 47(d1), 2019
PMID: 30289528
Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies.
Gardner PP, Watson RJ, Morgan XC, Draper JL, Finn RD, Morales SE, Stott MB., PeerJ 7(), 2019
PMID: 30631651
Reconstruction of the Genomes of Drug-Resistant Pathogens for Outbreak Investigation through Metagenomic Sequencing.
Mu A, Kwong JC, Isles NS, Gonçalves da Silva A, Schultz MB, Ballard SA, Lane CR, Carter GP, Williamson DA, Seemann T, Stinear TP, Howden BP., mSphere 4(1), 2019
PMID: 30651402
Choice of assembly software has a critical impact on virome characterisation.
Sutton TDS, Clooney AG, Ryan FJ, Ross RP, Hill C., Microbiome 7(1), 2019
PMID: 30691529
Kelpie: generating full-length 'amplicons' from whole-metagenome datasets.
Greenfield P, Tran-Dinh N, Midgley D., PeerJ 6(), 2019
PMID: 30723610
Assessing taxonomic metagenome profilers with OPAL.
Meyer F, Bremges A, Belmann P, Janssen S, McHardy AC, Koslicki D., Genome Biol 20(1), 2019
PMID: 30832730
Microbial abundance, activity and population genomic profiling with mOTUs2.
Milanese A, Mende DR, Paoli L, Salazar G, Ruscheweyh HJ, Cuenca M, Hingamp P, Alves R, Costea PI, Coelho LP, Schmidt TSB, Almeida A, Mitchell AL, Finn RD, Huerta-Cepas J, Bork P, Zeller G, Sunagawa S., Nat Commun 10(1), 2019
PMID: 30833550
The Wolbachia mobilome in Culex pipiens includes a putative plasmid.
Reveillaud J, Bordenstein SR, Cruaud C, Shaiber A, Esen ÖC, Weill M, Makoundou P, Lolans K, Watson AR, Rakotoarivony I, Bordenstein SR, Eren AM., Nat Commun 10(1), 2019
PMID: 30837458
Applying Genome-Resolved Metagenomics to Deconvolute the Halophilic Microbiome.
Uritskiy G, DiRuggiero J., Genes (Basel) 10(3), 2019
PMID: 30875864
Streaming histogram sketching for rapid microbiome analytics.
Rowe WP, Carrieri AP, Alcon-Giner C, Caim S, Shaw A, Sim K, Kroll JS, Hall LJ, Pyzer-Knapp EO, Winn MD., Microbiome 7(1), 2019
PMID: 30878035
Systematic benchmarking of omics computational tools.
Mangul S, Martin LS, Hill BL, Lam AK, Distler MG, Zelikovsky A, Eskin E, Flint J., Nat Commun 10(1), 2019
PMID: 30918265
Methods for automatic reference trees and multilevel phylogenetic placement.
Czech L, Barbera P, Stamatakis A., Bioinformatics 35(7), 2019
PMID: 30169747
Assessment of the structural and functional diversities of plant microbiota: Achievements and challenges - A review.
Hartmann A, Fischer D, Kinzel L, Chowdhury SP, Hofmann A, Baldani JI, Rothballer M., J Adv Res 19(), 2019
PMID: 31341665
MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data.
Plaza Oñate F, Le Chatelier E, Almeida M, Cervino ACL, Gauthier F, Magoulès F, Ehrlich SD, Pichaud M., Bioinformatics 35(9), 2019
PMID: 30252023
Ultra-deep, long-read nanopore sequencing of mock microbial community standards.
Nicholls SM, Quick JC, Tang S, Loman NJ., Gigascience 8(5), 2019
PMID: 31089679
NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language.
Coelho LP, Alves R, Monteiro P, Huerta-Cepas J, Freitas AT, Bork P., Microbiome 7(1), 2019
PMID: 31159881
Effect of Long-Term Farming Practices on Agricultural Soil Microbiome Members Represented by Metagenomically Assembled Genomes (MAGs) and Their Predicted Plant-Beneficial Genes.
Nelkner J, Henke C, Lin TW, Pätzold W, Hassa J, Jaenicke S, Grosch R, Pühler A, Sczyrba A, Schlüter A., Genes (Basel) 10(6), 2019
PMID: 31163637
MiCoP: microbial community profiling method for detecting viral and fungal organisms in metagenomic samples.
LaPierre N, Mangul S, Alser M, Mandric I, Wu NC, Koslicki D, Eskin E., BMC Genomics 20(suppl 5), 2019
PMID: 31167634
Taxonomy based performance metrics for evaluating taxonomic assignment methods.
Chen CY, Tang SL, Chou ST., BMC Bioinformatics 20(1), 2019
PMID: 31185897
Essential guidelines for computational method benchmarking.
Weber LM, Saelens W, Cannoodt R, Soneson C, Hapfelmeier A, Gardner PP, Boulesteix AL, Saeys Y, Robinson MD., Genome Biol 20(1), 2019
PMID: 31221194
Strain-level metagenomic assignment and compositional estimation for long reads with MetaMaps.
Dilthey AT, Jain C, Koren S, Phillippy AM., Nat Commun 10(1), 2019
PMID: 31296857
Benchmarking of alignment-free sequence comparison methods.
Zielezinski A, Girgis HZ, Bernard G, Leimeister CA, Tang K, Dencker T, Lau AK, Röhling S, Choi JJ, Waterman MS, Comin M, Kim SH, Vinga S, Almeida JS, Chan CX, James BT, Sun F, Morgenstern B, Karlowski WM., Genome Biol 20(1), 2019
PMID: 31345254
MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies.
Kang DD, Li F, Kirton E, Thomas A, Egan R, An H, Wang Z., PeerJ 7(), 2019
PMID: 31388474
To assemble or not to resemble-A validated Comparative Metatranscriptomics Workflow (CoMW).
Anwar MZ, Lanzen A, Bang-Andreasen T, Jacobsen CS., Gigascience 8(8), 2019
PMID: 31363751
Massive metagenomic data analysis using abundance-based machine learning.
Harris ZN, Dhungel E, Mosior M, Ahn TH., Biol Direct 14(1), 2019
PMID: 31370905
Targeted in situ metatranscriptomics for selected taxa from mesophilic and thermophilic biogas plants.
Stolze Y, Bremges A, Maus I, Pühler A, Sczyrba A, Schlüter A., Microb Biotechnol 11(4), 2018
PMID: 29205917
Proteomics and metabolomics for analysis of the dynamics of microbiota.
Van Belkum A, Broadwell D, Lovern D, Petersen L, Weinstock G, Dunne WM., Expert Rev Proteomics 15(2), 2018
PMID: 29284309
Multiscale Evolutionary Dynamics of Host-Associated Microbiomes.
Ferreiro A, Crook N, Gasparrini AJ, Dantas G., Cell 172(6), 2018
PMID: 29522743
Phylogenetic convolutional neural networks in metagenomics.
Fioravanti D, Giarratano Y, Maggio V, Agostinelli C, Chierici M, Jurman G, Furlanello C., BMC Bioinformatics 19(suppl 2), 2018
PMID: 29536822
Impact of sequencing depth on the characterization of the microbiome and resistome.
Zaheer R, Noyes N, Ortega Polo R, Cook SR, Marinier E, Van Domselaar G, Belk KE, Morley PS, McAllister TA., Sci Rep 8(1), 2018
PMID: 29651035
The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies
Angers-Loustau A, Petrillo M, Bengtsson-Palme J, Berendonk T, Blais B, Chan K, Coque TM, Hammer P, Heß S, Kagkli DM, Krumbiegel C, Lanza VF, Madec J, Naas T, O'Grady J, Paracchini V, Rossen JW, Ruppé E, Vamathevan J, Venturi V, Van den Eede G., 2018
PMID: PPR41805
The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies.
Angers-Loustau A, Petrillo M, Bengtsson-Palme J, Berendonk T, Blais B, Chan KG, Coque TM, Hammer P, Heß S, Kagkli DM, Krumbiegel C, Lanza VF, Madec JY, Naas T, O'Grady J, Paracchini V, Rossen JWA, Ruppé E, Vamathevan J, Venturi V, Van den Eede G., F1000Res 7(), 2018
PMID: 30026930
Flexible metagenome analysis using the MGX framework.
Jaenicke S, Albaum SP, Blumenkamp P, Linke B, Stoye J, Goesmann A., Microbiome 6(1), 2018
PMID: 29690922
Identifying Group-Specific Sequences for Microbial Communities Using Long k-mer Sequence Signatures.
Wang Y, Fu L, Ren J, Yu Z, Chen T, Sun F., Front Microbiol 9(), 2018
PMID: 29774017
Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.
Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, Huttley GA, Gregory Caporaso J., Microbiome 6(1), 2018
PMID: 29773078
Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy.
Sieber CMK, Probst AJ, Sharrar A, Thomas BC, Hess M, Tringe SG, Banfield JF., Nat Microbiol 3(7), 2018
PMID: 29807988
BLAST-based validation of metagenomic sequence assignments.
Bazinet AL, Ondov BD, Sommer DD, Ratnayake S., PeerJ 6(), 2018
PMID: 29868286
GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes.
Boyd JA, Woodcroft BJ, Tyson GW., Nucleic Acids Res 46(10), 2018
PMID: 29562347
ASaiM: a Galaxy-based framework to analyze microbiota data.
Batut B, Gravouil K, Defois C, Hiltemann S, Brugère JF, Peyretaillade E, Peyret P., Gigascience 7(6), 2018
PMID: 29790941
AMBER: Assessment of Metagenome BinnERs.
Meyer F, Hofmann P, Belmann P, Garrido-Oter R, Fritz A, Sczyrba A, McHardy AC., Gigascience 7(6), 2018
PMID: 29893851
ACI-1 beta-lactamase is widespread across human gut microbiomes in Negativicutes due to transposons harboured by tailed prophages.
Rands CM, Starikova EV, Brüssow H, Kriventseva EV, Govorun VM, Zdobnov EM., Environ Microbiol 20(6), 2018
PMID: 30014616
PriLive: privacy-preserving real-time filtering for next-generation sequencing.
Loka TP, Tausch SH, Dabrowski PW, Radonic A, Nitsche A, Renard BY., Bioinformatics 34(14), 2018
PMID: 29522157
Best practices for analysing microbiomes.
Knight R, Vrbanac A, Taylor BC, Aksenov A, Callewaert C, Debelius J, Gonzalez A, Kosciolek T, McCall LI, McDonald D, Melnik AV, Morton JT, Navas J, Quinn RA, Sanders JG, Swafford AD, Thompson LR, Tripathi A, Xu ZZ, Zaneveld JR, Zhu Q, Caporaso JG, Dorrestein PC., Nat Rev Microbiol 16(7), 2018
PMID: 29795328
Versatile genome assembly evaluation with QUAST-LG.
Mikheenko A, Prjibelski A, Saveliev V, Antipov D, Gurevich A., Bioinformatics 34(13), 2018
PMID: 29949969
Pan-genome Analysis of Ancient and Modern Salmonella enterica Demonstrates Genomic Stability of the Invasive Para C Lineage for Millennia.
Zhou Z, Lundstrøm I, Tran-Dien A, Duchêne S, Alikhan NF, Sergeant MJ, Langridge G, Fotakis AK, Nair S, Stenøien HK, Hamre SS, Casjens S, Christophersen A, Quince C, Thomson NR, Weill FX, Ho SYW, Gilbert MTP, Achtman M., Curr Biol 28(15), 2018
PMID: 30033331
Measuring metagenome diversity and similarity with Hill numbers.
Ma ZS, Li L., Mol Ecol Resour 18(6), 2018
PMID: 29985552
Analysis of sequencing strategies and tools for taxonomic annotation: Defining standards for progressive metagenomics.
Escobar-Zepeda A, Godoy-Lozano EE, Raggi L, Segovia L, Merino E, Gutiérrez-Rios RM, Juarez K, Licea-Navarro AF, Pardo-Lopez L, Sanchez-Flores A., Sci Rep 8(1), 2018
PMID: 30104688
Machine learning meets genome assembly.
Padovani de Souza K, Setubal JC, Ponce de Leon F de Carvalho AC, Oliveira G, Chateau A, Alves R., Brief Bioinform (), 2018
PMID: 30137230
PAIPline: pathogen identification in metagenomic and clinical next generation sequencing samples.
Andrusch A, Dabrowski PW, Klenner J, Tausch SH, Kohl C, Osman AA, Renard BY, Nitsche A., Bioinformatics 34(17), 2018
PMID: 30423069
MetaWRAP-a flexible pipeline for genome-resolved metagenomic data analysis.
Uritskiy GV, DiRuggiero J, Taylor J., Microbiome 6(1), 2018
PMID: 30219103
Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomes.
Alneberg J, Karlsson CMG, Divne AM, Bergin C, Homa F, Lindh MV, Hugerth LW, Ettema TJG, Bertilsson S, Andersson AF, Pinhassi J., Microbiome 6(1), 2018
PMID: 30266101
Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes.
Earl JP, Adappa ND, Krol J, Bhat AS, Balashov S, Ehrlich RL, Palmer JN, Workman AD, Blasetti M, Sen B, Hammond J, Cohen NA, Ehrlich GD, Mell JC., Microbiome 6(1), 2018
PMID: 30352611
RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification.
Nasko DJ, Koren S, Phillippy AM, Treangen TJ., Genome Biol 19(1), 2018
PMID: 30373669
Species-level functional profiling of metagenomes and metatranscriptomes.
Franzosa EA, McIver LJ, Rahnavard G, Thompson LR, Schirmer M, Weingart G, Lipson KS, Knight R, Caporaso JG, Segata N, Huttenhower C., Nat Methods 15(11), 2018
PMID: 30377376
Indexed variation graphs for efficient and accurate resistome profiling.
Rowe WPM, Winn MD., Bioinformatics 34(21), 2018
PMID: 29762644
Current progress and future opportunities in applications of bioinformatics for biodefense and pathogen detection: report from the Winter Mid-Atlantic Microbiome Meet-up, College Park, MD, January 10, 2018.
Meisel JS, Nasko DJ, Brubach B, Cepeda-Espinoza V, Chopyk J, Corrada-Bravo H, Fedarko M, Ghurye J, Javkar K, Olson ND, Shah N, Allard SM, Bazinet AL, Bergman NH, Brown A, Caporaso JG, Conlan S, DiRuggiero J, Forry SP, Hasan NA, Kralj J, Luethy PM, Milton DK, Ondov BD, Preheim S, Ratnayake S, Rogers SM, Rosovitz MJ, Sakowski EG, Schliebs NO, Sommer DD, Ternus KL, Uritskiy G, Zhang SX, Pop M, Treangen TJ., Microbiome 6(1), 2018
PMID: 30396371
The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies
Angers-Loustau A, Petrillo M, Bengtsson-Palme J, Berendonk T, Blais B, Chan K, Coque TM, Hammer P, Heß S, Kagkli DM, Krumbiegel C, Lanza VF, Madec J, Naas T, O'Grady J, Paracchini V, Rossen JW, Ruppé E, Vamathevan J, Venturi V, Van den Eede G., 2018
PMID: PPR64076
clubber: removing the bioinformatics bottleneck in big data analyses.
Miller M, Zhu C, Bromberg Y., J Integr Bioinform 14(2), 2017
PMID: 28609295
CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high precision.
Herath D, Tang SL, Tandon K, Ackland D, Halgamuge SK., BMC Bioinformatics 18(suppl 16), 2017
PMID: 29297295

52 References

Daten bereitgestellt von Europe PubMed Central.

A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data.
Coil D, Jospin G, Darling AE., Bioinformatics 31(4), 2014
PMID: 25338718
Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations.
Bendall ML, Stevens SL, Chan LK, Malfatti S, Schwientek P, Tremblay J, Schackwitz W, Martin J, Pati A, Bushnell B, Froula J, Kang D, Tringe SG, Bertilsson S, Moran MA, Shade A, Newton RJ, McMahon KD, Malmstrom RR., ISME J 10(7), 2016
PMID: 26744812
Metagenomic microbial community profiling using unique clade-specific marker genes.
Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C., Nat. Methods 9(8), 2012
PMID: 22688413
Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus.
Kashtan N, Roggensack SE, Rodrigue S, Thompson JW, Biller SJ, Coe A, Ding H, Marttinen P, Malmstrom RR, Stocker R, Follows MJ, Stepanauskas R, Chisholm SW., Science 344(6182), 2014
PMID: 24763590
The MG-RAST metagenomics database and portal in 2015.
Wilke A, Bischof J, Gerlach W, Glass E, Harrison T, Keegan KP, Paczian T, Trimble WL, Bagchi S, Grama A, Chaterji S, Meyer F., Nucleic Acids Res. 44(D1), 2015
PMID: 26656948
Enterotypes of the human gut microbiome.
Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, Bertalan M, Borruel N, Casellas F, Fernandez L, Gautier L, Hansen T, Hattori M, Hayashi T, Kleerebezem M, Kurokawa K, Leclerc M, Levenez F, Manichanh C, Nielsen HB, Nielsen T, Pons N, Poulain J, Qin J, Sicheritz-Ponten T, Tims S, Torrents D, Ugarte E, Zoetendal EG, Wang J, Guarner F, Pedersen O, de Vos WM, Brunak S, Dore J; MetaHIT Consortium, Antolin M, Artiguenave F, Blottiere HM, Almeida M, Brechot C, Cara C, Chervaux C, Cultrone A, Delorme C, Denariaz G, Dervyn R, Foerstner KU, Friss C, van de Guchte M, Guedon E, Haimet F, Huber W, van Hylckama-Vlieg J, Jamet A, Juste C, Kaci G, Knol J, Lakhdari O, Layec S, Le Roux K, Maguin E, Merieux A, Melo Minardi R, M'rini C, Muller J, Oozeer R, Parkhill J, Renault P, Rescigno M, Sanchez N, Sunagawa S, Torrejon A, Turner K, Vandemeulebrouck G, Varela E, Winogradsky Y, Zeller G, Weissenbach J, Ehrlich SD, Bork P., Nature 473(7346), 2011
PMID: 21508958
Durable coexistence of donor and recipient strains after fecal microbiota transplantation.
Li SS, Zhu A, Benes V, Costea PI, Hercog R, Hildebrand F, Huerta-Cepas J, Nieuwdorp M, Salojarvi J, Voigt AY, Zeller G, Sunagawa S, de Vos WM, Bork P., Science 352(6285), 2016
PMID: 27126044
IMG/M: integrated genome and metagenome comparative data analysis system.
Chen IA, Markowitz VM, Chu K, Palaniappan K, Szeto E, Pillay M, Ratner A, Huang J, Andersen E, Huntemann M, Varghese N, Hadjithomas M, Tennessen K, Nielsen T, Ivanova NN, Kyrpides NC., Nucleic Acids Res. 45(D1), 2016
PMID: 27738135
SILVA, RDP, Greengenes, NCBI and OTT - how do these taxonomies compare?
Balvociute M, Huson DH., BMC Genomics 18(Suppl 2), 2017
PMID: 28361695
Structure, function and diversity of the healthy human microbiome.
Human Microbiome Project Consortium, Huttenhower C, Gevers D, Knight R, Abubucker S, Badger JH, Chinwalla AT, Creasy HH, Earl AM, FitzGerald MG, Fulton RS, Giglio MG, Hallsworth-Pepin K, Lobos EA, Madupu R, Magrini V, Martin JC, Mitreva M, Muzny DM, Sodergren EJ, Versalovic J, Wollam AM, Worley KC, Wortman JR, Young SK, Zeng Q, Aagaard KM, Abolude OO, Allen-Vercoe E, Alm EJ, Alvarado L, Andersen GL, Anderson S, Appelbaum E, Arachchi HM, Armitage G, Arze CA, Ayvaz T, Baker CC, Begg L, Belachew T, Bhonagiri V, Bihan M, Blaser MJ, Bloom T, Bonazzi V, Brooks J, Buck GA, Buhay CJ, Busam DA, Campbell JL, Canon SR, Cantarel BL, Chain PS, Chen IM, Chen L, Chhibba S, Chu K, Ciulla DM, Clemente JC, Clifton SW, Conlan S, Crabtree J, Cutting MA, Davidovics NJ, Davis CC, DeSantis TZ, Deal C, Delehaunty KD, Dewhirst FE, Deych E, Ding Y, Dooling DJ, Dugan SP, Dunne WM, Durkin A, Edgar RC, Erlich RL, Farmer CN, Farrell RM, Faust K, Feldgarden M, Felix VM, Fisher S, Fodor AA, Forney LJ, Foster L, Di Francesco V, Friedman J, Friedrich DC, Fronick CC, Fulton LL, Gao H, Garcia N, Giannoukos G, Giblin C, Giovanni MY, Goldberg JM, Goll J, Gonzalez A, Griggs A, Gujja S, Haake SK, Haas BJ, Hamilton HA, Harris EL, Hepburn TA, Herter B, Hoffmann DE, Holder ME, Howarth C, Huang KH, Huse SM, Izard J, Jansson JK, Jiang H, Jordan C, Joshi V, Katancik JA, Keitel WA, Kelley ST, Kells C, King NB, Knights D, Kong HH, Koren O, Koren S, Kota KC, Kovar CL, Kyrpides NC, La Rosa PS, Lee SL, Lemon KP, Lennon N, Lewis CM, Lewis L, Ley RE, Li K, Liolios K, Liu B, Liu Y, Lo CC, Lozupone CA, Lunsford R, Madden T, Mahurkar AA, Mannon PJ, Mardis ER, Markowitz VM, Mavromatis K, McCorrison JM, McDonald D, McEwen J, McGuire AL, McInnes P, Mehta T, Mihindukulasuriya KA, Miller JR, Minx PJ, Newsham I, Nusbaum C, O'Laughlin M, Orvis J, Pagani I, Palaniappan K, Patel SM, Pearson M, Peterson J, Podar M, Pohl C, Pollard KS, Pop M, Priest ME, Proctor LM, Qin X, Raes J, Ravel J, Reid JG, Rho M, Rhodes R, Riehle KP, Rivera MC, Rodriguez-Mueller B, Rogers YH, Ross MC, Russ C, Sanka RK, Sankar P, Sathirapongsasuti J, Schloss JA, Schloss PD, Schmidt TM, Scholz M, Schriml L, Schubert AM, Segata N, Segre JA, Shannon WD, Sharp RR, Sharpton TJ, Shenoy N, Sheth NU, Simone GA, Singh I, Smillie CS, Sobel JD, Sommer DD, Spicer P, Sutton GG, Sykes SM, Tabbaa DG, Thiagarajan M, Tomlinson CM, Torralba M, Treangen TJ, Truty RM, Vishnivetskaya TA, Walker J, Wang L, Wang Z, Ward DV, Warren W, Watson MA, Wellington C, Wetterstrand KA, White JR, Wilczek-Boney K, Wu Y, Wylie KM, Wylie T, Yandava C, Ye L, Ye Y, Yooseph S, Youmans BP, Zhang L, Zhou Y, Zhu Y, Zoloth L, Zucker JD, Birren BW, Gibbs RA, Highlander SK, Methe BA, Nelson KE, Petrosino JF, Weinstock GM, Wilson RK, White O., Nature 486(7402), 2012
PMID: 22699609
TIPP: taxonomic identification and phylogenetic profiling.
Nguyen NP, Mirarab S, Liu B, Pop M, Warnow T., Bioinformatics 30(24), 2014
PMID: 25359891
MetaQUAST: evaluation of metagenome assemblies.
Mikheenko A, Saveliev V, Gurevich A., Bioinformatics 32(7), 2015
PMID: 26614127
The binning of metagenomic contigs for microbial physiology of mixed cultures.
Strous M, Kraft B, Bisdorf R, Tegetmeyer HE., Front Microbiol 3(), 2012
PMID: 23227024
Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing.
Koslicki D, Foucart S, Rosen G., Bioinformatics 29(17), 2013
PMID: 23786768
Metagenomics - a guide from sampling to data analysis.
Thomas T, Gilbert J, Meyer F., Microb Inform Exp 2(1), 2012
PMID: 22587947
Bioboxes: standardised containers for interchangeable bioinformatics software.
Belmann P, Droge J, Bremges A, McHardy AC, Sczyrba A, Barton MD., Gigascience 4(), 2015
PMID: 26473029
CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers.
Ounit R, Wanamaker S, Close TJ, Lonardi S., BMC Genomics 16(), 2015
PMID: 25879410
Functional overlap of the Arabidopsis leaf and root microbiota.
Bai Y, Muller DB, Srinivas G, Garrido-Oter R, Potthoff E, Rott M, Dombrowski N, Munch PC, Spaepen S, Remus-Emsermann M, Huttel B, McHardy AC, Vorholt JA, Schulze-Lefert P., Nature 528(7582), 2015
PMID: 26633631
An evaluation of the accuracy and speed of metagenome analysis tools.
Lindgreen S, Adair KL, Gardner PP., Sci Rep 6(), 2016
PMID: 26778510
A guide to enterotypes across the human body: meta-analysis of microbial community structures in human microbiome datasets.
Koren O, Knights D, Gonzalez A, Waldron L, Segata N, Knight R, Huttenhower C, Ley RE., PLoS Comput. Biol. 9(1), 2013
PMID: 23326225
EBI metagenomics in 2016--an expanding and evolving resource for the analysis and archiving of metagenomic data.
Mitchell A, Bucchini F, Cochrane G, Denise H, ten Hoopen P, Fraser M, Pesseat S, Potter S, Scheremetjew M, Sterk P, Finn RD., Nucleic Acids Res. 44(D1), 2015
PMID: 26582919
Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences.
Gao S, Sung WK, Nagarajan N., J. Comput. Biol. 18(11), 2011
PMID: 21929371
SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB.
Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glockner FO., Nucleic Acids Res. 35(21), 2007
PMID: 17947321
UniFrac: a new phylogenetic method for comparing microbial communities.
Lozupone C, Knight R., Appl. Environ. Microbiol. 71(12), 2005
PMID: 16332807
Microbiology: the road to strain-level identification.
Marx V., Nat. Methods 13(5), 2016
PMID: 27123815
Ray: simultaneous assembly of reads from a mix of high-throughput sequencing technologies.
Boisvert S, Laviolette F, Corbeil J., J. Comput. Biol. 17(11), 2010
PMID: 20958248
Recovering complete and draft population genomes from metagenome datasets.
Sangwan N, Xia F, Gilbert JA., Microbiome 4(), 2016
PMID: 26951112
DUDes: a top-down taxonomic profiler for metagenomics.
Piro VC, Lindner MS, Renard BY., Bioinformatics 32(15), 2016
PMID: 27153591
Metagenomics for pathogen detection in public health.
Miller RR, Montoya V, Gardy JL, Patrick DM, Tang P., Genome Med 5(9), 2013
PMID: 24050114
Natural history of the infant gut microbiome and impact of antibiotic treatment on bacterial strain diversity and stability.
Yassour M, Vatanen T, Siljander H, Hamalainen AM, Harkonen T, Ryhanen SJ, Franzosa EA, Vlamakis H, Huttenhower C, Gevers D, Lander ES, Knip M; DIABIMMUNE Study Group, Xavier RJ., Sci Transl Med 8(343), 2016
PMID: 27306663
Metagenomic species profiling using universal phylogenetic marker genes.
Sunagawa S, Mende DR, Zeller G, Izquierdo-Carrasco F, Berger SA, Kultima JR, Coelho LP, Arumugam M, Tap J, Nielsen HB, Rasmussen S, Brunak S, Pedersen O, Guarner F, de Vos WM, Wang J, Li J, Dore J, Ehrlich SD, Stamatakis A, Bork P., Nat. Methods 10(12), 2013
PMID: 24141494
Kraken: ultrafast metagenomic sequence classification using exact alignments.
Wood DE, Salzberg SL., Genome Biol. 15(3), 2014
PMID: 24580807
Protein signature-based estimation of metagenomic abundances including all domains of life and viruses.
Klingenberg H, Aßhauer KP, Lingner T, Meinicke P., Bioinformatics 29(8), 2013
PMID: 23418187
SEK: sparsity exploiting k-mer-based estimation of bacterial community composition.
Chatterjee S, Koslicki D, Dong S, Innocenti N, Cheng L, Lan Y, Vehkapera M, Skoglund M, Rasmussen LK, Aurell E, Corander J., Bioinformatics 30(17), 2014
PMID: 24812337
Genomic insights that advance the species definition for prokaryotes.
Konstantinidis KT, Tiedje JM., Proc. Natl. Acad. Sci. U.S.A. 102(7), 2005
PMID: 15701695
ARK: Aggregation of Reads by K-Means for Estimation of Bacterial Community Composition.
Koslicki D, Chatterjee S, Shahrivar D, Walker AW, Francis SC, Fraser LJ, Vehkapera M, Lan Y, Corander J., PLoS ONE 10(10), 2015
PMID: 26496191
Binning metagenomic contigs by coverage and composition.
Alneberg J, Bjarnason BS, de Bruijn I, Schirmer M, Quick J, Ijaz UZ, Lahti L, Loman NJ, Andersson AF, Quince C., Nat. Methods 11(11), 2014
PMID: 25218180
Accurate and fast estimation of taxonomic profiles from metagenomic shotgun sequences.
Liu B, Gibbons T, Ghodsi M, Treangen T, Pop M., BMC Genomics 12 Suppl 2(), 2011
PMID: 21989143
MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data.
Huson DH, Beier S, Flade I, Gorska A, El-Hadidi M, Mitra S, Ruscheweyh HJ, Tappu R., PLoS Comput. Biol. 12(6), 2016
PMID: 27327495
Use of simulated data sets to evaluate the fidelity of metagenomic processing methods.
Mavromatis K, Ivanova N, Barry K, Shapiro H, Goltsman E, McHardy AC, Rigoutsos I, Salamov A, Korzeniewski F, Land M, Lapidus A, Grigoriev I, Richardson P, Hugenholtz P, Kyrpides NC., Nat. Methods 4(6), 2007
PMID: 17468765
Meraculous: de novo genome assembly with short paired-end reads.
Chapman JA, Ho I, Sunkara S, Luo S, Schroth GP, Rokhsar DS., PLoS ONE 6(8), 2011
PMID: 21876754

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®

PMID: 28967888
PubMed | Europe PMC

Suchen in

Google Scholar