Application of a database-independent approach to assess the quality of operational taxonomic unit picking methods

mSystems

Volumn 1, Issue 2, 2016, Pages

  Schloss, Patrick D ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

16s rrna gene sequences; Bioinformatics; Environmental microbiology; Metagenomics; Microbial ecology; Microbiome; Mothur; Otu; Qiime

Indexed keywords

EID: 84992151320     PISSN: None     EISSN: 23795077     Source Type: Journal    
DOI: 10.1128/mSystems.00027-16     Document Type: Review

References (29)

1. Schloss PD, Westcott SL. 2011. Assessing and improving methods used in operational taxonomic unit-based approaches for 16S rRNA gene sequence analysis. Appl Environ Microbiol 77:3219 -3226. http://dx.doi.org/10.1128/aem.02810-10.
2. Westcott SL, Schloss PD. 2015. De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units. PeerJ 3:e1487. http://dx.doi.org/10.7717/peerj.1487.
3. He Y, Caporaso JG, Jiang X-T, Sheng H-F, Huse SM, Rideout JR, Edgar RC, Kopylova E, Walters WA, Knight R, Zhou H-W. 2015. Stability of operational taxonomic units: An important but neglected property for analyzing microbial diversity. Microbiome 3:20. http://dx.doi.org/10.1186/s40168-015-0081-x.
4. Kopylova E, Navas-Molina JA, Mercier C, Xu ZZ, Mahé F, He Y, Zhou H-W, Rognes T, Caporaso JG, Knight R. 2016. Open-source sequence clustering methods improve the state of the art. mSystems 1:e00003-15. http://dx.doi.org/10.1128/msystems.00003-15.
5. Edgar RC. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996-998. http://dx.doi.org/10.1038/nmeth.2604.
6. Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M. 2014. Swarm: robust and fast clustering method for amplicon-based studies. PeerJ 2:e593. http://dx.doi.org/10.7717/peerj.593.
7. Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M. 2015. Swarm v2: highly-scalable and high-resolution amplicon clustering. PeerJ 3:e1420. http://dx.doi.org/10.7717/peerj.1420.
8. Barriuso J, Valverde JR, Mellado RP. 2011. Estimation of bacterial diversity using next generation sequencing of 16S rDNA: A comparison of different workflows. BMC Bioinformatics 12:473. http://dx.doi.org/10.1186/1471-2105-12-473.
9. Bonder MJ, Abeln S, Zaura E, Brandt BW. 2012. Comparing clustering and pre-processing in taxonomy analysis. Bioinformatics 28:2891-2897. http://dx.doi.org/10.1093/bioinformatics/bts552.
10. Chen W, Zhang CK, Cheng Y, Zhang S, Zhao H. 2013. A comparison of methods for clustering 16S rRNA sequences into OTUs. PLoS One 8:e70837. http://dx.doi.org/10.1371/journal.pone.0070837.
11. Huse SM, Welch DM, Morrison HG, Sogin ML. 2010. Ironing out the wrinkles in the rare biosphere through improved OTU clustering. Environ Microbiol 12:1889 -1898. http://dx.doi.org/10.1111/j.1462 -2920.2010.02193.x.
12. May A, Abeln S, Crielaard W, Heringa J, Brandt BW. 2014. Unraveling the outcome of 16S rDNA-based taxonomy analysis through mock data and simulations. Bioinformatics 30:1530 -1538. http://dx.doi.org/10.1093/bioinformatics/btu085.
13. Cai Y, Sun Y. 2011. ESPRIT-tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time. Nucleic Acids Res 39:e95. http://dx.doi.org/10.1093/nar/gkr349.
14. Sun Y, Cai Y, Huse SM, Knight R, Farmerie WG, Wang X, Mai V. 2012. A large-scale benchmark study of existing algorithms for taxonomyindependent microbial community analysis. Brief Bioinform 13:107-121. http://dx.doi.org/10.1093/bib/bbr009.
15. White JR, Navlakha S, Nagarajan N, Ghodsi M-R, Kingsford C, Pop M. 2010. Alignment and clustering of phylogenetic markers-implications for microbial diversity studies. BMC Bioinformatics 11:152. http://dx.doi.org/10.1186/1471-2105-11-152.
16. Al-Ghalith GA, Montassier E, Ward HN, Knights D. 2016. NINJA-OPS: fast accurate marker gene alignment using concatenated ribosomes. PLoS Comput Biol 12:e1004658. http://dx.doi.org/10.1371/journal.pcbi.1004658.
17. Sun Y, Cai Y, Liu L, Yu F, Farrell ML, McKendree W, Farmerie W. 2009. ESPRIT: estimating species richness using large collections of 16S rRNA pyrosequences. Nucleic Acids Res 37:e76. http://dx.doi.org/10.1093/nar/gkp285.
18. 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 H-W, Knight R, Caporaso JG. 2014. Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences. PeerJ 2:e545. http://dx.doi.org/10.7717/peerj.545.
19. Schmidt TS, Matias Rodrigues JF, von Mering C. 2015. Limits to robustness and reproducibility in the demarcation of operational taxonomic units. Environ Microbiol 17:1689 -1706. http://dx.doi.org/10.1111/1462-2920.12610.
20. Matthews B. 1975. Comparison of the predicted and observed secondary structure of t4 phage lysozyme. Biochim Biophys Acta 405:442-451. http://dx.doi.org/10.1016/0005-2795(75)90109-9.
21. Roesch LF, Fulthorpe RR, Riva A, Casella G, Hadwin AK, Kent AD, Daroub SH, Camargo FA, Farmerie WG, Triplett EW. 2007. Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J 1:283-290. http://dx.doi.org/10.1038/ismej.2007.53.
22. Schloss PD, Schubert AM, Zackular JP, Iverson KD, Young VB, Petrosino JF. 2012. Stabilization of the murine gut microbiome following weaning. Gut Microbes 3:383-393. http://dx.doi.org/10.4161/gmic.21008.
23. Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glöckner FO. 2007. Silva: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35:7188-7196. http://dx.doi.org/10.1093/nar/gkm864.
24. Schloss PD. 2016. Application of database-independent approach to assess the quality of OTU picking methods. GitHub https://github.com/SchlossLab/Schloss-Cluster-PeerJ-2015.
25. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537-7541. http://dx.doi.org/10.1128/aem.01541-09.
26. Rognes T, Mahé F, Flouri T, McDonald D. 2015. Vsearch: VSEARCH 1.4.0. Zenodo, European Organization for Nuclear Research, Geneva, Switzerland.
27. Albanese D, Fontana P, De Filippo C, Cavalieri D, Donati C. 2015. Micca: A complete and accurate software for taxonomic profiling of metagenomic data. Sci Rep 5:9743. http://dx.doi.org/10.1038/srep09743.
28. Kopylova E, Noé L, Touzet H. 2012. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics 28:3211-3217. http://dx.doi.org/10.1093/bioinformatics/bts611.
29. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335-336. http://dx.doi.org/10.1038/nmeth.f.303.