Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/2737
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dc.contributor.authorKochan, Necla-
dc.contributor.authorTütüncü, Gözde Yazgı-
dc.contributor.authorSmyth, Gordon K.-
dc.contributor.authorGandoffo, Luke C.-
dc.contributor.authorGiner, Goeknur-
dc.date.accessioned2023-06-16T14:48:25Z-
dc.date.available2023-06-16T14:48:25Z-
dc.date.issued2019-
dc.identifier.issn2167-8359-
dc.identifier.urihttps://doi.org/10.7717/peerj.8260-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/2737-
dc.description.abstractClassification on the basis of gene expression data derived from RNA-seq promises to become an important part of modern medicine. We propose a new classification method based on a model where the data is marginally negative binomial but dependent, thereby incorporating the dependence known to be present between measurements from different genes. The method, called qtQDA, works by first performing a quantile transformation (qt) then applying Gaussian quadratic discriminant analysis (QDA) using regularized covariance matrix estimates. We show that qtQDA has excellent performance when applied to real data sets and has advantages over some existing approaches. An R package implementing the method is also available on https://github.com/goknurginer/qtQDA.en_US
dc.description.sponsorshipScientific and Technical Research Council of Turkey [TUBITAK 2214/A-1059B141601270]; Australian National Health and Medical Research Council [1054618, 1154970]; Cancer Therapeutics CRC; Victorian State Government Operational Infrastructure Support; Australian Government NHMRC IRIIS; Smyth Lab funds; National Health and Medical Research Council of Australia [1154970] Funding Source: NHMRCen_US
dc.description.sponsorshipThis work was supported by the Scientific and Technical Research Council of Turkey (TUBITAK 2214/A-1059B141601270) and by the Australian National Health and Medical Research Council (Program Grant 1054618 and Fellowship 1154970 to Gordon K. Smyth), the Cancer Therapeutics CRC, Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIIS. Funding for the article processing fee was provided by Smyth Lab funds. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en_US
dc.language.isoenen_US
dc.publisherPeerj Incen_US
dc.relation.ispartofPeerjen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectClassificationen_US
dc.subjectGene expressionen_US
dc.subjectRNA-seqen_US
dc.subjectDependent count dataen_US
dc.subjectNegative binomial distributionen_US
dc.subjectQuadratic discriminant analysisen_US
dc.subjectCovariance-Matrixen_US
dc.subjectClassificationen_US
dc.titleQtqda: Quantile Transformed Quadratic Discriminant Analysis for High-Dimensional Rna-Seq Dataen_US
dc.typeArticleen_US
dc.identifier.doi10.7717/peerj.8260-
dc.identifier.pmid31976167en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authoridTütüncü, G.Yazgı/0000-0002-9363-6141-
dc.authoridKoçhan, Necla/0000-0003-2355-4826-
dc.authoridSmyth, Gordon/0000-0001-9221-2892-
dc.authorwosidTütüncü, G.Yazgı/AAP-6520-2021-
dc.authorwosidKoçhan, Necla/AAA-4147-2021-
dc.authorwosidSmyth, Gordon/B-5276-2008-
dc.authorwosidKochan, Necla/AAA-4191-2021-
dc.identifier.volume7en_US
dc.identifier.wosWOS:000503384400006en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ3-
dc.identifier.wosqualityQ2-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypeArticle-
item.cerifentitytypePublications-
crisitem.author.dept02.02. Mathematics-
crisitem.author.dept02.02. Mathematics-
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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