Publication:
Unbiased Taxonomic Annotation of Metagenomic Samples

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dc.contributor.authorFosso, Bruno
dc.contributor.authorPesole, Graziano
dc.contributor.authorRossello, Francesc
dc.contributor.authorValiente, Gabriel
dc.date.accessioned2024-09-06T09:56:47Z
dc.date.available2024-09-06T09:56:47Z
dc.date.issued2018-03
dc.description.abstractThe classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under the receiver operating characteristic (ROC) curve and F-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample.en
dc.description.sponsorshipPartially supported by INMARE (H2020-BG-2014-2, GA 634486), EMBRIC (H2020-INFRADEV-1-2014-1, GA 654008), EXCELERATE (H2020-INFRADEV-1-2015-1, GA 676559), PRIN 2010 (MIUR, Ministero dell'Istruzione, Universita e Ricerca of Italy), and by the Spanish Ministry of Economy and Competitiveness and European Regional Development Fund project DPI2015-67082-P (MINECO/FEDER).es_ES
dc.format.number3es_ES
dc.format.page348-360es_ES
dc.format.volume25es_ES
dc.identifier.citationFosso Bruno, Pesole Graziano,Rossello Francesc, Valiente Gabriel. Unbiased Taxonomic Annotation of Metagenomic Samples. J Comput Biol. 2018 Mar;25(3):348-360. Epub 2017 Oct 13.en
dc.identifier.doi10.1089/cmb.2017.0144
dc.identifier.e-issn1557-8666es_ES
dc.identifier.issn1066-5277
dc.identifier.journalJournal of Computational Biologyes_ES
dc.identifier.otherhttp://hdl.handle.net/20.500.13003/9391
dc.identifier.pubmedID29028181es_ES
dc.identifier.puiL627115432
dc.identifier.scopus2-s2.0-85045469782
dc.identifier.urihttps://hdl.handle.net/20.500.12105/22643
dc.identifier.wos429742800009
dc.language.isoengen
dc.publisherMary Ann Lieberten
dc.relation.publisherversionhttps://dx.doi.org/10.1089/cmb.2017.0144en
dc.rights.accessRightsopen accessen
dc.rights.licenseAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectClassification
dc.subjectCorrelation
dc.subjectMetagenomics
dc.subjectSet cover
dc.subjectTaxonomic annotation
dc.subject.decsFilogenia*
dc.subject.decsHumanos*
dc.subject.decsProgramas Informáticos*
dc.subject.decsMicrobiota*
dc.subject.decsCódigo de Barras del ADN Taxonómico*
dc.subject.decsMetagenoma*
dc.subject.meshMicrobiota*
dc.subject.meshSoftware*
dc.subject.meshMetagenome*
dc.subject.meshDNA Barcoding, Taxonomic*
dc.subject.meshPhylogeny*
dc.subject.meshHumans*
dc.titleUnbiased Taxonomic Annotation of Metagenomic Samplesen
dc.typeresearch articleen
dspace.entity.typePublication
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