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2015-06-15Zeitschriftenartikel DOI: 10.1093/bioinformatics/btv236
MSProGene: integrative proteogenomics beyond six-frames and single nucleotide polymorphisms
dc.contributor.authorZickmann, Franziska
dc.contributor.authorRenard, Bernhard Y.
dc.date.accessioned2018-05-07T18:18:04Z
dc.date.available2018-05-07T18:18:04Z
dc.date.created2015-06-30
dc.date.issued2015-06-15none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/re2eGznhm0J6/PDF/26P3vWDTpfO8U.pdf
dc.identifier.urihttp://edoc.rki.de/176904/2080
dc.description.abstractOngoing advances in high-throughput technologies have facilitated accurate proteomic measurements and provide a wealth of information on genomic and transcript level. In proteogenomics, this multi-omics data is combined to analyze unannotated organisms and to allow more accurate sample-specific predictions. Existing analysis methods still mainly depend on six-frame translations or reference protein databases that are extended by transcriptomic information or known single nucleotide polymorphisms (SNPs). However, six-frames introduce an artificial sixfold increase of the target database and SNP integration requires a suitable database summarizing results from previous experiments. We overcome these limitations by introducing MSProGene, a new method for integrative proteogenomic analysis based on customized RNA-Seq driven transcript databases. MSProGene is independent from existing reference databases or annotated SNPs and avoids large six-frame translated databases by constructing sample-specific transcripts. In addition, it creates a network combining RNA-Seq and peptide information that is optimized by a maximum-flow algorithm. It thereby also allows resolving the ambiguity of shared peptides for protein inference. We applied MSProGene on three datasets and show that it facilitates a database-independent reliable yet accurate prediction on gene and protein level and additionally identifies novel genes.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut
dc.subjectAnimalseng
dc.subjectAlgorithmseng
dc.subjectMass Spectrometryeng
dc.subjectSoftwareeng
dc.subjectDatabases Geneticeng
dc.subjectPeptides/chemistryeng
dc.subjectProteins/geneticseng
dc.subjectGene Expression Profilingeng
dc.subjectPolymorphism Single Nucleotideeng
dc.subjectSequence Analysis RNAeng
dc.subjectProteomics/methodseng
dc.subjectBartonella/geneticseng
dc.subjectFilarioidea/geneticseng
dc.subjectGenomics/methodseng
dc.subjectProteins/chemistryeng
dc.subjectProteins/metabolismeng
dc.subject.ddc610 Medizin
dc.titleMSProGene: integrative proteogenomics beyond six-frames and single nucleotide polymorphisms
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10039801
dc.identifier.doi10.1093/bioinformatics/btv236
dc.identifier.doihttp://dx.doi.org/10.25646/2005
local.edoc.container-titleBioinformatics
local.edoc.container-textZickmann, F., Renard, B.Y. MSProGene: Integrative proteogenomics beyond six-frames and single nucleotide polymorphisms (2015) Bioinformatics, 31 (12), pp. i106-i115.
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/31/12/i106
local.edoc.container-publisher-nameOxford University Press
local.edoc.container-volume31
local.edoc.container-issue12
local.edoc.container-year2015

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