{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:38:16Z","timestamp":1761896296097},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,4,29]],"date-time":"2016-04-29T00:00:00Z","timestamp":1461888000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2016,4,29]],"date-time":"2016-04-29T00:00:00Z","timestamp":1461888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"SCK-CEN","award":["PhD fellowship"],"award-info":[{"award-number":["PhD fellowship"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>The development of high-throughput sequencing technologies has revolutionized the field of microbial ecology via the sequencing of phylogenetic marker genes (e.g. 16S rRNA gene\u00a0amplicon sequencing). Denoising, the removal of sequencing errors, is an important step in preprocessing amplicon sequencing data. The increasing popularity of the Illumina MiSeq platform for these applications requires the development of appropriate denoising methods.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The newly proposed denoising algorithm IPED includes a machine learning method which predicts potentially erroneous positions in sequencing reads based on a combination of quality metrics. Subsequently, this information is used to group those error-containing reads with correct reads, resulting in error-free consensus reads. This is achieved by masking potentially erroneous positions during this clustering step. Compared to the second best algorithm available, IPED detects double the amount of errors. Reducing the error rate had a positive effect on the clustering of reads in operational taxonomic units, with an almost perfect correspondence between the number of clusters and the theoretical number of species present in the mock communities.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Our algorithm IPED is a powerful denoising tool for correcting sequencing errors in Illumina MiSeq 16S rRNA gene\u00a0amplicon sequencing data. Apart from significantly reducing the error rate of the sequencing reads, it has also a beneficial effect on their clustering into operational taxonomic units. IPED is freely available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/science.sckcen.be\/en\/Institutes\/EHS\/MCB\/MIC\/Bioinformatics\/\">http:\/\/science.sckcen.be\/en\/Institutes\/EHS\/MCB\/MIC\/Bioinformatics\/<\/jats:ext-link>.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-016-1061-2","type":"journal-article","created":{"date-parts":[[2016,4,29]],"date-time":"2016-04-29T06:27:03Z","timestamp":1461911223000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["IPED: a highly efficient denoising tool for Illumina MiSeq Paired-end 16S rRNA\u00a0gene amplicon sequencing data"],"prefix":"10.1186","volume":"17","author":[{"given":"Mohamed","family":"Mysara","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalie","family":"Leys","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeroen","family":"Raes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pieter","family":"Monsieurs","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,4,29]]},"reference":[{"key":"1061_CR1","doi-asserted-by":"publisher","first-page":"7537","DOI":"10.1128\/AEM.01541-09","volume":"75","author":"PD Schloss","year":"2009","unstructured":"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. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75:7537\u201341.","journal-title":"Appl Environ Microbiol"},{"key":"1061_CR2","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1038\/nmeth.f.303","volume":"7","author":"JG Caporaso","year":"2010","unstructured":"Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pe\u00f1a 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. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335\u20136.","journal-title":"Nat Methods"},{"key":"1061_CR3","doi-asserted-by":"publisher","first-page":"996","DOI":"10.1038\/nmeth.2604","volume":"10","author":"RC Edgar","year":"2013","unstructured":"Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods. 2013;10:996\u20138.","journal-title":"Nat Methods"},{"key":"1061_CR4","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1038\/nbt.2198","volume":"30","author":"NJ Loman","year":"2012","unstructured":"Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, Wain J, Pallen MJ. Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol. 2012;30:434\u20139.","journal-title":"Nat Biotechnol"},{"key":"1061_CR5","doi-asserted-by":"publisher","first-page":"5112","DOI":"10.1128\/AEM.01043-13","volume":"79","author":"JJ Kozich","year":"2013","unstructured":"Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol. 2013;79:5112\u201320.","journal-title":"Appl Environ Microbiol"},{"key":"1061_CR6","doi-asserted-by":"publisher","first-page":"R83","DOI":"10.1186\/gb-2009-10-8-r83","volume":"10","author":"M Kircher","year":"2009","unstructured":"Kircher M, Stenzel U, Kelso J. Improved base calling for the Illumina Genome Analyzer using machine learning strategies. Genome Biol. 2009;10:R83.","journal-title":"Genome Biol"},{"key":"1061_CR7","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1038\/nature07517","volume":"456","author":"DR Bentley","year":"2008","unstructured":"Bentley DR, Balasubramanian S, Swerdlow HP, et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature. 2008;456:53\u20139.","journal-title":"Nature"},{"key":"1061_CR8","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1186\/1471-2105-9-431","volume":"9","author":"J Rougemont","year":"2008","unstructured":"Rougemont J, Amzallag A, Iseli C, Farinelli L, Xenarios I, Naef F. Probabilistic base calling of Solexa sequencing data. BMC Bioinformatics. 2008;9:431.","journal-title":"BMC Bioinformatics"},{"issue":"Suppl 5","key":"1061_CR9","doi-asserted-by":"publisher","first-page":"S1","DOI":"10.1186\/1471-2105-14-S5-S1","volume":"14","author":"M Allhoff","year":"2013","unstructured":"Allhoff M, Sch\u00f6nhuth A, Martin M, Costa IG, Rahmann S, Marschall T. Discovering motifs that induce sequencing errors. BMC Bioinformatics. 2013;14 Suppl 5:S1.","journal-title":"BMC Bioinformatics"},{"key":"1061_CR10","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1093\/dnares\/dst054","volume":"21","author":"IJ Tsai","year":"2014","unstructured":"Tsai IJ, Hunt M, Holroyd N, Huckvale T, Berriman M, Kikuchi T. Summarizing specific profiles in Illumina sequencing from whole-genome amplified DNA. DNA Res. 2014;21:243\u201354.","journal-title":"DNA Res"},{"issue":"6","key":"1061_CR11","doi-asserted-by":"publisher","first-page":"e37","DOI":"10.1093\/nar\/gku1341","volume":"43","author":"M Schirmer","year":"2015","unstructured":"Schirmer M, Ijaz UZ, D\u2019Amore R, Hall N, Sloan WT, Quince C. Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform. Nucleic Acids Res. 2015;43(6):e37.","journal-title":"Nucleic Acids Res"},{"key":"1061_CR12","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1038\/nmeth0910-668b","volume":"7","author":"J Reeder","year":"2010","unstructured":"Reeder J, Knight R. Rapidly denoising pyrosequencing amplicon reads by exploiting rank-abundance distributions. Nat Methods. 2010;7:668\u20139.","journal-title":"Nat Methods"},{"key":"1061_CR13","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1186\/1471-2105-12-38","volume":"12","author":"C Quince","year":"2011","unstructured":"Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ. Removing noise from pyrosequenced amplicons. BMC Bioinformatics. 2011;12:38.","journal-title":"BMC Bioinformatics"},{"key":"1061_CR14","doi-asserted-by":"publisher","first-page":"1889","DOI":"10.1111\/j.1462-2920.2010.02193.x","volume":"12","author":"SM Huse","year":"2010","unstructured":"Huse SM, Welch DM, Morrison HG, Sogin ML. Ironing out the wrinkles in the rare biosphere through improved OTU clustering. Environ Microbiol. 2010;12:1889\u201398.","journal-title":"Environ Microbiol"},{"key":"1061_CR15","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1038\/nmeth.1990","volume":"9","author":"L Bragg","year":"2012","unstructured":"Bragg L, Stone G, Imelfort M, Hugenholtz P, Tyson GW. Fast, accurate error-correction of amplicon pyrosequences using Acacia. Nat Methods. 2012;9:425\u20136.","journal-title":"Nat Methods"},{"key":"1061_CR16","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1186\/s12859-015-0520-5","volume":"16","author":"M Mysara","year":"2015","unstructured":"Mysara M, Leys N, Raes J, Monsieurs P. NoDe: a fast error-correction algorithm for pyrosequencing amplicon reads. BMC Bioinformatics. 2015;16:88.","journal-title":"BMC Bioinformatics"},{"key":"1061_CR17","doi-asserted-by":"publisher","first-page":"3476","DOI":"10.1093\/bioinformatics\/btv401","volume":"31","author":"RC Edgar","year":"2015","unstructured":"Edgar RC, Flyvbjerg H. Error filtering, pair assembly, and error correction for next-generation sequencing reads. Bioinformatics. 2015;31:3476\u201382.","journal-title":"Bioinformatics"},{"key":"1061_CR18","doi-asserted-by":"publisher","first-page":"2957","DOI":"10.1093\/bioinformatics\/btr507","volume":"27","author":"T Mago\u010d","year":"2011","unstructured":"Mago\u010d T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957\u201363.","journal-title":"Bioinformatics"},{"key":"1061_CR19","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1186\/1471-2105-13-31","volume":"13","author":"AP Masella","year":"2012","unstructured":"Masella AP, Bartram AK, Truszkowski JM, Brown DG, Neufeld JD. PANDAseq: paired-end assembler for illumina sequences. BMC Bioinformatics. 2012;13:31.","journal-title":"BMC Bioinformatics"},{"key":"1061_CR20","doi-asserted-by":"publisher","first-page":"2870","DOI":"10.1093\/bioinformatics\/bts563","volume":"28","author":"B Liu","year":"2012","unstructured":"Liu B, Yuan J, Yiu S-M, Li Z, Xie Y, Chen Y, Shi Y, Zhang H, Li Y, Lam T-W, Luo R. COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly. Bioinformatics. 2012;28:2870\u20134.","journal-title":"Bioinformatics"},{"key":"1061_CR21","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1093\/bioinformatics\/btt593","volume":"30","author":"J Zhang","year":"2014","unstructured":"Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics. 2014;30:614\u201320.","journal-title":"Bioinformatics"},{"key":"1061_CR22","doi-asserted-by":"publisher","first-page":"e94249","DOI":"10.1371\/journal.pone.0094249","volume":"9","author":"MC Nelson","year":"2014","unstructured":"Nelson MC, Morrison HG, Benjamino J, Grim SL, Graf J. Analysis, optimization and verification of Illumina-generated 16S rRNA gene amplicon surveys. PLoS One. 2014;9:e94249.","journal-title":"PLoS One"},{"key":"1061_CR23","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1186\/1471-2164-12-245","volume":"12","author":"A Gilles","year":"2011","unstructured":"Gilles A, Megl\u00e9cz E, Pech N, Ferreira S, Malausa T, Martin J-F. Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing. BMC Genomics. 2011;12:245.","journal-title":"BMC Genomics"},{"key":"1061_CR24","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","volume":"215","author":"SF Altschul","year":"1990","unstructured":"Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403\u201310.","journal-title":"J Mol Biol"},{"key":"1061_CR25","doi-asserted-by":"publisher","first-page":"4673","DOI":"10.1093\/nar\/22.22.4673","volume":"22","author":"JD Thompson","year":"1994","unstructured":"Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673\u201380.","journal-title":"Nucleic Acids Res"},{"key":"1061_CR26","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, National H, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH. The WEKA Data Mining Software : An Update. SIGKDD Explor. 2009;11:10\u20138.","journal-title":"SIGKDD Explor"},{"key":"1061_CR27","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1016\/0005-2795(75)90109-9","volume":"405","author":"BW Matthews","year":"1975","unstructured":"Matthews BW. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta. 1975;405:442\u201351.","journal-title":"Biochim Biophys Acta"},{"key":"1061_CR28","doi-asserted-by":"publisher","first-page":"e27310","DOI":"10.1371\/journal.pone.0027310","volume":"6","author":"PD Schloss","year":"2011","unstructured":"Schloss PD, Gevers D, Westcott SL. Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies. PLoS One. 2011;6:e27310.","journal-title":"PLoS One"},{"key":"1061_CR29","doi-asserted-by":"publisher","first-page":"e90","DOI":"10.1093\/nar\/gkr344","volume":"39","author":"K Nakamura","year":"2011","unstructured":"Nakamura K, Oshima T, Morimoto T, Ikeda S, Yoshikawa H, Shiwa Y, Ishikawa S, Linak MC, Hirai A, Takahashi H, Altaf-Ul-Amin M, Ogasawara N, Kanaya S. Sequence-specific error profile of Illumina sequencers. Nucleic Acids Res. 2011;39:e90.","journal-title":"Nucleic Acids Res"},{"key":"1061_CR30","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1111\/j.1462-2920.2009.02051.x","volume":"12","author":"V Kunin","year":"2010","unstructured":"Kunin V, Engelbrektson A, Ochman H, Hugenholtz P. Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ Microbiol. 2010;12:118\u201323.","journal-title":"Environ Microbiol"},{"key":"1061_CR31","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1128\/AEM.02896-14","volume":"81","author":"M Mysara","year":"2015","unstructured":"Mysara M, Saeys Y, Leys N, Raes J, Monsieurs P. CATCh, an ensemble classifier for chimera detection in 16S rRNA sequencing studies. Appl Environ Microbiol. 2015;81:1573\u201384.","journal-title":"Appl Environ Microbiol"},{"key":"1061_CR32","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1126\/science.1146689","volume":"318","author":"JA Huber","year":"2007","unstructured":"Huber JA, Mark Welch DB, Morrison HG, Huse SM, Neal PR, Butterfield DA, Sogin ML. Microbial population structures in the deep marine biosphere. Science. 2007;318:97\u2013100.","journal-title":"Science"},{"key":"1061_CR33","doi-asserted-by":"publisher","first-page":"12115","DOI":"10.1073\/pnas.0605127103","volume":"103","author":"ML Sogin","year":"2006","unstructured":"Sogin ML, Morrison HG, Huber JA, Mark Welch D, Huse SM, Neal PR, Arrieta JM, Herndl GJ. Microbial diversity in the deep sea and the underexplored \u201crare biosphere\u201d. Proc Natl Acad Sci U S A. 2006;103:12115\u201320.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"1061_CR34","doi-asserted-by":"publisher","first-page":"e114804","DOI":"10.1371\/journal.pone.0114804","volume":"9","author":"P Jeraldo","year":"2014","unstructured":"Jeraldo P, Kalari K, Chen X, Bhavsar J, Mangalam A, White B, Nelson H, Kocher J-P, Chia N. IM-TORNADO: A Tool for Comparison of 16S Reads from Paired-End Libraries. PLoS One. 2014;9:e114804.","journal-title":"PLoS One"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1061-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-016-1061-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1061-2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1061-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T18:03:50Z","timestamp":1706810630000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-016-1061-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,29]]},"references-count":34,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,12]]}},"alternative-id":["1061"],"URL":"https:\/\/doi.org\/10.1186\/s12859-016-1061-2","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,4,29]]},"assertion":[{"value":"12 March 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 April 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"192"}}