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dc.contributor.authorChambers, Matthew C.en_US
dc.contributor.authorJagtap, Pratik D.en_US
dc.contributor.authorJohnson, James E.en_US
dc.contributor.authorMcGowan, Thomasen_US
dc.contributor.authorKumar, Praveenen_US
dc.contributor.authorOnsongo, Getiriaen_US
dc.contributor.authorGuerrero, Candace R.en_US
dc.contributor.authorBarsnes, Haralden_US
dc.contributor.authorVaudel, Marcen_US
dc.contributor.authorMartens, Lennarten_US
dc.contributor.authorGrüning, Björnen_US
dc.contributor.authorCooke, Ira R.en_US
dc.contributor.authorHeydarian, Mohammaden_US
dc.contributor.authorReddy, Karen L.en_US
dc.contributor.authorGriffin, Timothy J.en_US
dc.date.accessioned2020-06-03T07:30:12Z
dc.date.available2020-06-03T07:30:12Z
dc.date.issued2017
dc.PublishedChambers, Jagtap, Johnson JE, McGowan, Kumar P, Onsongo, Guerrero, Barsnes H, Vaudel M, Martens L, Grüning, Cooke IR, Heydarian, Reddy, Griffin. An accessible proteogenomics informatics resource for cancer researchers. Cancer Research. 2017;77(21):e43-e46eng
dc.identifier.issn0008-5472
dc.identifier.issn1538-7445
dc.identifier.urihttps://hdl.handle.net/1956/22439
dc.description.abstractProteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry–based proteomics data to directly identify expressed, variant protein sequences that may have functional roles in cancer. This approach is computationally intensive, requiring integration of disparate software tools into sophisticated workflows, challenging its adoption by nonexpert, bench scientists. To address this need, we have developed an extensible, Galaxy-based resource aimed at providing more researchers access to, and training in, proteogenomic informatics. Our resource brings together software from several leading research groups to address two foundational aspects of proteogenomics: (i) generation of customized, annotated protein sequence databases from RNA-Seq data; and (ii) accurate matching of tandem mass spectrometry data to putative variants, followed by filtering to confirm their novelty. Directions for accessing software tools and workflows, along with instructional documentation, can be found at z.umn.edu/canresgithub.en_US
dc.language.isoengeng
dc.publisherAmerican Association for Cancer Researcheng
dc.titleAn accessible proteogenomics informatics resource for cancer researchersen_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2019-11-11T14:30:43Z
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2017 American Association for Cancer Research.
dc.identifier.doihttps://doi.org/10.1158/0008-5472.can-17-0331
dc.identifier.cristin1530001
dc.source.journalCancer Research
dc.relation.projectBergens forskningsstiftelse: BFS2016REK02
dc.relation.projectNorges forskningsråd: 251235


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