A method for analyzing censored survival phenotype with gene expression data

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dc.contributor.authorWu, Tongtong
dc.contributor.authorSun, Wei
dc.contributor.authorYuan, Shinsheng
dc.contributor.authorChen, Chun-Houh
dc.contributor.authorLi, Ker-Chau
dc.date.accessioned2021-12-02T18:10:37Z
dc.date.available2021-12-02T18:10:37Z
dc.date.issued2008-10-06
dc.description.abstractSurvival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles and survival time. However, due to the censoring effects of survival time and the high dimensionality of gene expression data, effective and unbiased selection of a gene expression signature to predict survival probabilities requires further study. We propose a method for an integrated study of survival time and gene expression. This method can be summarized as a two-step procedure: in the first step, a moderate number of genes are pre-selected using correlation or liquid association (LA). Imputation and transformation methods are employed for the correlation/LA calculation. In the second step, the dimension of the predictors is further reduced using the modified sliced inverse regression for censored data (censorSIR). The new method is tested via both simulated and real data. For the real data application, we employed a set of 295 breast cancer patients and found a linear combination of 22 gene expression profiles that are significantly correlated with patients' survival rate. By an appropriate combination of feature selection and dimension reduction, we find a method of identifying gene expression signatures which is effective for survival prediction.en_US
dc.identifierhttps://doi.org/10.13016/sadj-ijxk
dc.identifier.citationWu, T., Sun, W., Yuan, S. et al. A method for analyzing censored survival phenotype with gene expression data. BMC Bioinformatics 9, 417 (2008).en_US
dc.identifier.urihttp://hdl.handle.net/1903/28181
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.isAvailableAtEpidemiology & Biostatistics
dc.relation.isAvailableAtSchool of Public Health
dc.relation.isAvailableAtDigital Repository at the University of Maryland (DRUM)
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)
dc.subjectSurvival Timeen_US
dc.subjectGene Expression Dataen_US
dc.subjectSurvival Probabilityen_US
dc.subjectGene Expression Signatureen_US
dc.subjectProjection Directionen_US
dc.titleA method for analyzing censored survival phenotype with gene expression dataen_US
dc.typeArticleen_US

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