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Items: 1 to 20 of 67


Swarm: robust and fast clustering method for amplicon-based studies.

Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M.

PeerJ. 2014 Sep 25;2:e593. doi: 10.7717/peerj.593. eCollection 2014.


Swarm v2: highly-scalable and high-resolution amplicon clustering.

Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M.

PeerJ. 2015 Dec 10;3:e1420. doi: 10.7717/peerj.1420. eCollection 2015.


Comparison of three clustering approaches for detecting novel environmental microbial diversity.

Forster D, Dunthorn M, Stoeck T, Mahé F.

PeerJ. 2016 Feb 25;4:e1692. doi: 10.7717/peerj.1692. eCollection 2016.


GeFaST: An improved method for OTU assignment by generalising Swarm's fastidious clustering approach.

Müller R, Nebel ME.

BMC Bioinformatics. 2018 Sep 12;19(1):321. doi: 10.1186/s12859-018-2349-1.


Open-Source Sequence Clustering Methods Improve the State Of the Art.

Kopylova E, Navas-Molina JA, Mercier C, Xu ZZ, Mahé F, He Y, Zhou HW, Rognes T, Caporaso JG, Knight R.

mSystems. 2016 Feb 9;1(1). pii: e00003-15. eCollection 2016 Jan-Feb.


MICCA: a complete and accurate software for taxonomic profiling of metagenomic data.

Albanese D, Fontana P, De Filippo C, Cavalieri D, Donati C.

Sci Rep. 2015 May 19;5:9743. doi: 10.1038/srep09743.


Two-stage clustering (TSC): a pipeline for selecting operational taxonomic units for the high-throughput sequencing of PCR amplicons.

Jiang XT, Zhang H, Sheng HF, Wang Y, He Y, Zou F, Zhou HW.

PLoS One. 2012;7(1):e30230. doi: 10.1371/journal.pone.0030230. Epub 2012 Jan 11.


bioOTU: An Improved Method for Simultaneous Taxonomic Assignments and Operational Taxonomic Units Clustering of 16s rRNA Gene Sequences.

Chen SY, Deng F, Huang Y, Jia X, Liu YP, Lai SJ.

J Comput Biol. 2016 Apr;23(4):229-38. doi: 10.1089/cmb.2015.0214. Epub 2016 Mar 7.


Inconsistent Denoising and Clustering Algorithms for Amplicon Sequence Data.

Koskinen K, Auvinen P, Björkroth KJ, Hultman J.

J Comput Biol. 2015 Aug;22(8):743-51. doi: 10.1089/cmb.2014.0268. Epub 2014 Dec 19.


A Clustering Optimization Strategy for Molecular Taxonomy Applied to Planktonic Foraminifera SSU rDNA.

Göker M, Grimm GW, Auch AF, Aurahs R, Kučera M.

Evol Bioinform Online. 2010 Sep 9;6:97-112.


Efficient and Accurate OTU Clustering with GPU-Based Sequence Alignment and Dynamic Dendrogram Cutting.

Nguyen TD, Schmidt B, Zheng Z, Kwoh CK.

IEEE/ACM Trans Comput Biol Bioinform. 2015 Sep-Oct;12(5):1060-73. doi: 10.1109/TCBB.2015.2407574.


Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

He Y, Caporaso JG, Jiang XT, Sheng HF, Huse SM, Rideout JR, Edgar RC, Kopylova E, Walters WA, Knight R, Zhou HW.

Microbiome. 2015 May 20;3:20. doi: 10.1186/s40168-015-0081-x. eCollection 2015. Erratum in: Microbiome. 2015;3:34.


A Comparison Study of Validity Indices on Swarm-Intelligence-Based Clustering.

Rui Xu, Jie Xu, Wunsch DC.

IEEE Trans Syst Man Cybern B Cybern. 2012 Aug;42(4):1243-56. doi: 10.1109/TSMCB.2012.2188509. Epub 2012 Mar 15.


Assessing and improving methods used in operational taxonomic unit-based approaches for 16S rRNA gene sequence analysis.

Schloss PD, Westcott SL.

Appl Environ Microbiol. 2011 May;77(10):3219-26. doi: 10.1128/AEM.02810-10. Epub 2011 Mar 18.


Clustering of fungal community internal transcribed spacer sequence data obscures taxonomic diversity.

Yamamoto N, Bibby K.

Environ Microbiol. 2014 Aug;16(8):2491-500. doi: 10.1111/1462-2920.12390. Epub 2014 Mar 4.


Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences.

Rideout JR, He Y, Navas-Molina JA, Walters WA, Ursell LK, Gibbons SM, Chase J, McDonald D, Gonzalez A, Robbins-Pianka A, Clemente JC, Gilbert JA, Huse SM, Zhou HW, Knight R, Caporaso JG.

PeerJ. 2014 Aug 21;2:e545. doi: 10.7717/peerj.545. eCollection 2014.


Evaluation of water sampling methodologies for amplicon-based characterization of bacterial community structure.

Staley C, Gould TJ, Wang P, Phillips J, Cotner JB, Sadowsky MJ.

J Microbiol Methods. 2015 Jul;114:43-50. doi: 10.1016/j.mimet.2015.05.003. Epub 2015 May 6.


mPUMA: a computational approach to microbiota analysis by de novo assembly of operational taxonomic units based on protein-coding barcode sequences.

Links MG, Chaban B, Hemmingsen SM, Muirhead K, Hill JE.

Microbiome. 2013 Aug 15;1(1):23. doi: 10.1186/2049-2618-1-23.


Massively parallel tag sequencing reveals the complexity of anaerobic marine protistan communities.

Stoeck T, Behnke A, Christen R, Amaral-Zettler L, Rodriguez-Mora MJ, Chistoserdov A, Orsi W, Edgcomb VP.

BMC Biol. 2009 Nov 3;7:72. doi: 10.1186/1741-7007-7-72.

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