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dc.contributor.authorChoi, Meena
dc.contributor.authorEren-Doğu, Zeynep Filiz
dc.contributor.authorColangelo, Christopher
dc.contributor.authorCottrell, John
dc.contributor.authorHoopmann, Michael R.
dc.contributor.authorKapp, Eugene A.
dc.contributor.authorVitek, Olga
dc.date.accessioned2020-11-20T14:53:37Z
dc.date.available2020-11-20T14:53:37Z
dc.date.issued2017
dc.identifier.issn1535-3893
dc.identifier.issn1535-3907
dc.identifier.urihttps://doi.org/10.1021/acs.jproteome.6b00881
dc.identifier.urihttps://hdl.handle.net/20.500.12809/2047
dc.descriptionWOS: 000393539600054en_US
dc.descriptionPubMed ID: 27990823en_US
dc.description.abstractDetection of differentially abundant proteins in label-free quantitative shotgun liquid chromatography tandem mass spectrometry (LC-MS/MS) experiments requires a series of computational steps that identify and quantify LC-MS features. It also requires statistical analyses that distinguish systematic changes in abundance between conditions from artifacts of biological and technical variation. The 2015 study of the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) aimed to evaluate the effects of the statistical analysis on the accuracy of the results. The study used LC tandem mass spectra acquired from a controlled mixture, and made the data available to anonymous volunteer participants. The participants used methods of their choice to detect differentially abundant proteins, estimate the associated fold changes, and characterize the uncertainty of the results. The study found that multiple strategies (including the use of spectral counts versus peak intensities, and various software tools) could lead to accurate results, and that the performance was primarily determined by the analysts' expertise. This manuscript summarizes the outcome of the study, and provides representative examples of good computational and statistical practice. The data set generated as part of this study is publicly available.en_US
dc.description.sponsorshipNIH NINDSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Neurological Disorders & Stroke (NINDS) [P30 NS050276]; National Institute of General Medical SciencesUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [R01GM087221]; Center for Systems Biology [2P50 GM076547]; ABRF; NIH Shared Instrumentation GrantUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [RR027990]; NATIONAL CENTER FOR RESEARCH RESOURCESUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Center for Research Resources (NCRR) [S10RR027990] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, R01GM087221, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547, P50GM076547] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKEUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Neurological Disorders & Stroke (NINDS) [P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276, P30NS050276] Funding Source: NIH RePORTER; Direct For Computer & Info Scie & EnginrNational Science Foundation (NSF)NSF - Directorate for Computer & Information Science & Engineering (CISE) [1544542] Funding Source: National Science Foundation; Division of Computing and Communication FoundationsNational Science Foundation (NSF)NSF - Directorate for Computer & Information Science & Engineering (CISE) [1544542] Funding Source: National Science Foundationen_US
dc.description.sponsorshipWe thank the participants of the iPRG 2015 study for their work in preparing the submissions. We thank Steven Blais and Jingjing Deng from the Neubert Lab (Mass Spectrometry Core for Neuroscience), Skirball Institute, NYU School of Medicine, for the LC-MS/MS analysis to produce the data for this study. We acknowledge support from the ABRF and NIH Shared Instrumentation Grant RR027990, NIH NINDS grant P30 NS050276, the National Institute of General Medical Sciences under grant R01GM087221, and 2P50 GM076547/Center for Systems Biology.en_US
dc.item-language.isoengen_US
dc.publisherAmer Chemical Socen_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMass Spectrometryen_US
dc.subjectLC-MS/MSen_US
dc.subjectQuantitative Proteomicsen_US
dc.subjectBioinformaticsen_US
dc.subjectStatisticsen_US
dc.subjectDifferential Abundanceen_US
dc.titleABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC-MS/MS Experimentsen_US
dc.item-typearticleen_US
dc.contributor.departmentMÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.contributor.institutionauthorEren-Doğu, Zeynep Filiz
dc.identifier.doi10.1021/acs.jproteome.6b00881
dc.identifier.volume16en_US
dc.identifier.issue2en_US
dc.identifier.startpage945en_US
dc.identifier.endpage957en_US
dc.relation.journalJournal of Proteome Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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