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Phylogeny-aware identification and correction of taxonomically mislabeled sequences

Kozlov, Alexey M.; Zhang, Jiajie; Yilmaz, Pelin; Gloeckner, Frank Oliver; Stamatakis, Alexandros 1
1 Institut für Theoretische Informatik (ITI), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Molecular sequences in public databases are mostly annotated by the submitting authors without further validation. This procedure can generate erroneous taxonomic sequence labels. Mislabeled sequences are hard to identify, and they can induce downstream errors because new sequences are typically annotated using existing ones. Furthermore, taxonomic mislabelings in reference sequence databases can bias metagenetic studies which rely on the taxonomy. Despite significant efforts to improve the quality of taxonomic annotations, the curation rate is low because of the labor-intensive manual curation process. Here, we present SATIVA, a phylogeny-aware method to automatically identify taxonomically mislabeled sequences (‘mislabels’) using statistical models of evolution. We use the Evolutionary Placement Algorithm (EPA) to detect and score sequences whose taxonomic annotation is not supported by the underlying phylogenetic signal, and automatically propose a corrected taxonomic classification for those. Using simulated data, we show that our method attains high accuracy for identification (96.9% sensitivity/91.7% precision) as well as correction (94.9% sensitivity/89.9% precision) of mislabels. ... mehr


Volltext §
DOI: 10.5445/IR/1000057736
Originalveröffentlichung
DOI: 10.1093/nar/gkw396
Scopus
Zitationen: 68
Web of Science
Zitationen: 64
Dimensions
Zitationen: 93
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2016
Sprache Englisch
Identifikator ISSN: 0305-1048
urn:nbn:de:swb:90-577369
KITopen-ID: 1000057736
Erschienen in Nucleic acids research
Verlag Oxford University Press (OUP)
Band 44
Heft 11
Seiten 5022-5033
Nachgewiesen in Web of Science
Dimensions
PubMed
Scopus
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