Show simple item record

dc.contributor.authorZhao, Qiang ( )en_US
dc.contributor.authorSun, Jianguo ( )en_US
dc.date.accessioned2010-05-05T19:03:53Z
dc.date.available2012-02-24T10:17:55Z
dc.date.issued2007-05-29en_US
dc.identifier.citationZhao, Q., & Sun, J. (2007). Cox survival analysis of microarray gene expression data using correlation principal component regression. Statistical Applications in Genetics and Molecular Biology, 6(1).
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/3821
dc.description.abstractStatistical analysis of microarray gene expression data has recently attracted a great deal of attention. One problem of interest is to relate genes to survival outcomes of patients with the purpose of building regression models for the prediction of future patients' survival based on their gene expression data. For this, several authors have discussed the use of the proportional hazards or Cox model after reducing the dimension of the gene expression data. This paper presents a new approach to conduct the Cox survival analysis of microarray gene expression data with the focus on models' predictive ability. The method modifies the correlation principal component regression (Sun, 1995) to handle the censoring problem of survival data. The results based on simulated data and a set of publicly available data on diffuse large B-cell lymphoma show that the proposed method works well in terms of models' robustness and predictive ability in comparison with some existing partial least squares approaches. Also, the new approach is simpler and easy to implement.en_US
dc.formatText
dc.format.extent16 pages
dc.format.medium1 file (.pdf)
dc.language.isoen
dc.publisherThe Berkeley Electronic Press
dc.sourceStatistical Applications in Genetics and Molecular Biology, 2007, Vol. 6, No. 1, Article 16.
dc.subjectSurvival analysisen_US
dc.subjectCox modelen_US
dc.subjectMicroarray gene expression dataen_US
dc.subjectCorrelation principalen_US
dc.subjectComponent regressionen_US
dc.subject.classificationBiology, generalen_US
dc.subject.classificationMathematicsen_US
dc.titleCox Survival Analysis of Microarray Gene Expression Data Using Correlation Principal Component Regressionen_US
dc.typepublishedVersion
txstate.documenttypeArticle
dc.rights.holder© 2007 The Berkeley Electronic Press.
dc.identifier.doihttps://doi.org/10.2202/1544-6115.1153
dc.description.departmentMathematics


Download

Thumbnail

This item appears in the following Collection(s)

Show simple item record