Zur Kurzanzeige

2014-06-15Zeitschriftenartikel DOI: 10.1093/bioinformatics/btu267
Pipasic: similarity and expression correction for strain-level identification and quantification in metaproteomics
dc.contributor.authorPenzlin, Anke
dc.contributor.authorLindner, Martin S.
dc.contributor.authorDöllinger, Jörg
dc.contributor.authorDabrowski, Piotr Wojtek
dc.contributor.authorNitsche, Andreas
dc.contributor.authorRenard, Bernhard Y.
dc.date.accessioned2018-05-07T17:46:01Z
dc.date.available2018-05-07T17:46:01Z
dc.date.created2014-06-30
dc.date.issued2014-06-15none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/reN3MIHhStg/PDF/225HqnnSD0tE.pdf
dc.identifier.urihttp://edoc.rki.de/176904/1908
dc.description.abstractMotivation: Metaproteomic analysis allows studying the interplay of organisms or functional groups and has become increasingly popular also for diagnostic purposes. However, difficulties arise owing to the high sequence similarity between related organisms. Further, the state of conservation of proteins between species can be correlated with their expression level, which can lead to significant bias in results and interpretation. These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions. Results: We introduce Pipasic (peptide intensity-weighted proteome abundance similarity correction) as a tool that corrects identification and spectral counting-based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. Pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor, as demonstrated on examples of viral diagnostics and an acid mine drainage dataset.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut, Biologische Sicherheit
dc.subjectAlgorithmseng
dc.subjectMass Spectrometryeng
dc.subjectSoftwareeng
dc.subjectPeptides/chemistryeng
dc.subjectBacterial Proteins/metabolismeng
dc.subjectEnvironmental Microbiologyeng
dc.subjectCowpox virus/classificationeng
dc.subjectProteome/chemistryeng
dc.subjectProteome/metabolismeng
dc.subjectProteomics/methodseng
dc.subject.ddc610 Medizin
dc.titlePipasic: similarity and expression correction for strain-level identification and quantification in metaproteomics
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10036806
dc.identifier.doi10.1093/bioinformatics/btu267
dc.identifier.doihttp://dx.doi.org/10.25646/1833
local.edoc.container-titleBioinformatics
local.edoc.container-textThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://bioinformatics.oxfordjournals.org/content/30/12/i149.abstract
local.edoc.container-publisher-nameOxford University Press
local.edoc.container-volume30
local.edoc.container-issue12
local.edoc.container-year2014

Zur Kurzanzeige