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    A method for analyzing censored survival phenotype with gene expression data

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    1471-2105-9-417.pdf (369.9Kb)
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    Date
    2008-10-06
    Author
    Wu, Tongtong
    Sun, Wei
    Yuan, Shinsheng
    Chen, Chun-Houh
    Li, Ker-Chau
    Citation
    Wu, T., Sun, W., Yuan, S. et al. A method for analyzing censored survival phenotype with gene expression data. BMC Bioinformatics 9, 417 (2008).
    DRUM DOI
    https://doi.org/10.13016/sadj-ijxk
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    Abstract
    Survival 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.
    URI
    http://hdl.handle.net/1903/28181
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    • Epidemiology & Biostatistics Research Works

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    DRUM is brought to you by the University of Maryland Libraries
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