Piphillin predicts metagenomic composition and dynamics from DADA2-corrected 16S rDNA sequences

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dc.contributor.authorNarayan, Nicole R.
dc.contributor.authorWeinmaier, Thomas
dc.contributor.authorLaserna-Mendieta, Emilio J.
dc.contributor.authorClaesson, Marcus J.
dc.contributor.authorShanahan, Fergus
dc.contributor.authorDabbagh, Karim
dc.contributor.authorIwai, Shoko
dc.contributor.authorDeSantis, Todd Z.
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderSecond Genome Inc., USAen
dc.date.accessioned2020-01-30T12:40:43Z
dc.date.available2020-01-30T12:40:43Z
dc.date.issued2020-01-17
dc.date.updated2020-01-22T11:44:50Z
dc.description.abstractShotgun metagenomic sequencing reveals the potential in microbial communities. However, lower-cost 16S ribosomal RNA (rRNA) gene sequencing provides taxonomic, not functional, observations. To remedy this, we previously introduced Piphillin, a software package that predicts functional metagenomic content based on the frequency of detected 16S rRNA gene sequences corresponding to genomes in regularly updated, functionally annotated genome databases. Piphillin (and similar tools) have previously been evaluated on 16S rRNA data processed by the clustering of sequences into operational taxonomic units (OTUs). New techniques such as amplicon sequence variant error correction are in increased use, but it is unknown if these techniques perform better in metagenomic content prediction pipelines, or if they should be treated the same as OTU data in respect to optimal pipeline parameters.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid56en
dc.identifier.citationNarayan, N. R., Weinmaier, T., Laserna-Mendieta, E. J., Claesson, M. J., Shanahan, F., Dabbagh, K., Iwai, S. and DeSantis, T. Z. (2020) 'Piphillin predicts metagenomic composition and dynamics from DADA2-corrected 16S rDNA sequences', BMC Genomics, 21(1), 56 (12pp). doi: 10.1186/s12864-019-6427-1en
dc.identifier.doi10.1186/s12864-019-6427-1en
dc.identifier.endpage12en
dc.identifier.issn1471-2164
dc.identifier.issued1en
dc.identifier.journaltitleBMC Genomicsen
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/9596
dc.identifier.volume21en
dc.language.isoenen
dc.publisherBioMed Central Ltd.en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Starting Investigator Research Grant (SIRG)/11/SIRG/B2162/IE/Molecular diagnostics and metatranscriptomics of colonic bacteria in inflammatory bowel disease/en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2273/IE/Alimentary Pharmabiotic Centre (APC) - Interfacing Food & Medicine/en
dc.relation.urihttps://doi.org/10.1186/s12864-019-6427-1
dc.rights© 2020, the Authors. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.subjectMetagenomicsen
dc.subjectPhylogenetic analysisen
dc.subjectSequence alignmenten
dc.subjectShotgun sequencingen
dc.subjectGenomic databasesen
dc.titlePiphillin predicts metagenomic composition and dynamics from DADA2-corrected 16S rDNA sequencesen
dc.typeArticle (peer-reviewed)en
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