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dc.contributor.authorLahesmaa-Korpinen, Anna-Maria
dc.contributor.authorCarlson, Scott M.
dc.contributor.authorWhite, Forest M.
dc.contributor.authorHautaniemi, Sampsa
dc.date.accessioned2013-01-08T19:01:08Z
dc.date.available2013-01-08T19:01:08Z
dc.date.issued2010-09
dc.date.submitted2010-07
dc.identifier.issn1615-9853
dc.identifier.issn1615-9861
dc.identifier.urihttp://hdl.handle.net/1721.1/76211
dc.description.abstractMS/MS is a widely used method for proteome-wide analysis of protein expression and PTMs. The thousands of MS/MS spectra produced from a single experiment pose a major challenge for downstream analysis. Standard programs, such as MASCOT, provide peptide assignments for many of the spectra, including identification of PTM sites, but these results are plagued by false-positive identifications. In phosphoproteomic experiments, only a single peptide assignment is typically available to support identification of each phosphorylation site, and hence minimizing false positives is critical. Thus, tedious manual validation is often required to increase confidence in the spectral assignments. We have developed phoMSVal, an open-source platform for managing MS/MS data and automatically validating identified phosphopeptides. We tested five classification algorithms with 17 extracted features to separate correct peptide assignments from incorrect ones using over 2600 manually curated spectra. The naïve Bayes algorithm was among the best classifiers with an AUC value of 97% and PPV of 97% for phosphotyrosine data. This classifier required only three features to achieve a 76% decrease in false positives as compared with MASCOT while retaining 97% of true positives. This algorithm was able to classify an independent phosphoserine/threonine data set with AUC value of 93% and PPV of 91%, demonstrating the applicability of this method for all types of phospho-MS/MS data. PhoMSVal is available at http://csbi.ltdk.helsinki.fi/phomsval.en_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowship Programen_US
dc.language.isoen_US
dc.publisherWiley Blackwellen_US
dc.relation.isversionofhttp://dx.doi.org/10.1002/pmic.200900727en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourcePMCen_US
dc.titleIntegrated data management and validation platform for phosphorylated tandem mass spectrometry dataen_US
dc.typeArticleen_US
dc.identifier.citationLahesmaa-Korpinen, Anna-Maria et al. “Integrated Data Management and Validation Platform for Phosphorylated Tandem Mass Spectrometry Data.” PROTEOMICS 10.19 (2010): 3515–3524.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentKoch Institute for Integrative Cancer Research at MITen_US
dc.contributor.mitauthorCarlson, Scott M.
dc.contributor.mitauthorWhite, Forest M.
dc.relation.journalPROTEOMICSen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsLahesmaa-Korpinen, Anna-Maria; Carlson, Scott M.; White, Forest M.; Hautaniemi, Sampsaen
dc.identifier.orcidhttps://orcid.org/0000-0002-1545-1651
dspace.mitauthor.errortrue
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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