Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1220
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dc.contributor.authorKochan, Necla-
dc.contributor.authorTütüncü, Gözde Yazgı-
dc.contributor.authorGiner, Goknur-
dc.date.accessioned2023-06-16T12:59:26Z-
dc.date.available2023-06-16T12:59:26Z-
dc.date.issued2021-
dc.identifier.issn0957-4174-
dc.identifier.issn1873-6793-
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2020.114200-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/1220-
dc.description.abstractRecent developments in the next-generation sequencing based on RNA-sequencing (RNA-Seq) allow researchers to measure the expression levels of thousands of genes for multiple samples simultaneously. In order to analyze these kinds of data sets, many classification models have been proposed in the literature. Most of the existing classifiers assume that genes are independent; however, this is not a realistic approach for real RNA-Seq classification problems. For this reason, some other classification methods, which incorporates the dependence structure between genes into a model, are proposed. Quantile transformed Quadratic Discriminant Analysis (qtQDA) proposed recently is one of those classifiers, which estimates covariance matrix by Maximum Likelihood Estimator. However, MLE may not reflect the real dependence between genes. For this reason, we propose a new approach based on local dependence function to estimate the covariance matrix to be used in the qtQDA classification model. This new approach assumes the dependencies between genes are locally defined rather than complete dependency. The performances of qtQDA classifier based on two different covariance matrix estimates are compared over two real RNA-Seq data sets, in terms of classification error rates. The results show that using local dependence function approach yields a better estimate of covariance matrix and increases the performance of qtQDA classifier.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; National Health and Medical Research Council of Australia [1154970] Funding Source: NHMRCen_US
dc.description.sponsorshipWe thank Prof. Dr. Gordon K. Smyth, Prof. Dr. Terry Speed and Luke C. Gandolfo for their support and suggestions and WEHI Bioinformatics division for using their resources. This 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. 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.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems Wıth Applıcatıonsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectRNA-seqen_US
dc.subjectGene expressionen_US
dc.subjectLocal Covariance matrixen_US
dc.subjectClassificationen_US
dc.subjectQuadratic Discriminant Analysisen_US
dc.subjectLogistic-Regressionen_US
dc.titleA New Local Covariance Matrix Estimation for the Classification of Gene Expression Profiles in High Dimensional Rna-Seq Dataen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.eswa.2020.114200-
dc.identifier.scopus2-s2.0-85095566328en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authoridTütüncü, G.Yazgı/0000-0002-9363-6141-
dc.authoridKoçhan, Necla/0000-0003-2355-4826-
dc.authorwosidTütüncü, G.Yazgı/AAP-6520-2021-
dc.authorwosidKoçhan, Necla/AAA-4147-2021-
dc.authorwosidKochan, Necla/AAA-4191-2021-
dc.authorscopusid56218351000-
dc.authorscopusid26436326500-
dc.authorscopusid56304121500-
dc.identifier.volume167en_US
dc.identifier.wosWOS:000640531100035en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
dc.identifier.wosqualityQ1-
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:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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