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dc.contributor.author
Bokulich, Nicholas
dc.contributor.author
Rideout, Jai Ram
dc.contributor.author
Kopylova, Evguenia
dc.contributor.author
Bolyen, Evan
dc.contributor.author
Patnode, Jessica
dc.contributor.author
Ellett, Zach
dc.contributor.author
McDonald, Daniel
dc.contributor.author
Wolfe, Benjamin
dc.contributor.author
Maurice, Corinne F.
dc.contributor.author
Dutton, Rachel J.
dc.contributor.author
Turnbaugh, Peter J.
dc.contributor.author
Knight, Rob
dc.contributor.author
Caporaso, J. Gregory
dc.date.accessioned
2020-08-18T06:55:44Z
dc.date.available
2020-08-12T10:05:14Z
dc.date.available
2020-08-18T06:55:44Z
dc.date.issued
2015-07
dc.identifier.issn
2167-9843
dc.identifier.other
10.7287/peerj.preprints.934v2
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/431158
dc.description.abstract
Background: Taxonomic classification of marker-gene (i.e., amplicon) sequences represents an important step for molecular identification of microorganisms. Results: We present three advances in our ability to assign and interpret taxonomic classifications of short marker gene sequences: two new methods for taxonomy assignment, which reduce runtime up to two-fold and achieve high-precision genus-level assignments; an evaluation of classification methods that highlights differences in performance with different marker genes and at different levels of taxonomic resolution; and an extensible framework for evaluating and optimizing new classification methods, which we hope will serve as a model for standardized and reproducible bioinformatics methods evaluations. Conclusions: Our new methods are accessible in QIIME 1.9.0, and our evaluation framework will support ongoing optimization of classification methods to complement rapidly evolving short-amplicon sequencing and bioinformatics technologies. Static versions of all of the analysis notebooks generated with this framework, which contain all code and analysis results, can be viewed at http://bit.ly/srta-012 .
en_US
dc.language.iso
en
en_US
dc.publisher
PeerJ
en_US
dc.title
A standardized, extensible framework for optimizing classification improves marker-gene taxonomic assignments
en_US
dc.type
Working Paper
ethz.journal.title
PeerJ Preprints
ethz.journal.volume
3
en_US
ethz.pages.start
e934v2
en_US
ethz.size
45 p.
en_US
ethz.publication.place
Corte Madera, CA
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::02701 - Inst.f. Lebensmittelwiss.,Ernährung,Ges. / Institute of Food, Nutrition, and Health::09714 - Bokulich, Nicholas / Bokulich, Nicholas
en_US
ethz.date.deposited
2020-08-12T10:05:22Z
ethz.source
BATCH
ethz.eth
no
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-08-18T06:55:57Z
ethz.rosetta.lastUpdated
2022-03-29T02:56:17Z
ethz.rosetta.versionExported
true
ethz.COinS
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